Storing data in a dispersed storage network

ABSTRACT

A method begins by a dispersed storage (DS) processing module transmitting a set of write commands for storing a set of encoded data slices in storage units of a dispersed storage network (DSN) and determining whether at least a first threshold number of write responses have been received within a response time period. When the at least the first threshold number of the write responses have been received within the response time period, the method continues with the DS processing module determining whether a total number of responses have been received within another response time period. When the total number of responses have not been received within the other response time period, the method continues with the DS processing module issuing a sub-set of write commit commands corresponding to a response number of encoded data slices for which a response was received.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility patent application claims priority pursuant to35 U.S.C. §119(e) to U.S. Provisional Application No. 61/841,625,entitled “PRIORITIZING TASKS IN A DISPERSED STORAGE NETWORK”, filed Jul.1, 2013, which is hereby incorporated herein by reference in itsentirety and made part of the present U.S. Utility patent applicationfor all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

NOT APPLICABLE

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

NOT APPLICABLE

BACKGROUND OF THE INVENTION

1. Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersed storage of data and distributed taskprocessing of data.

2. Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system in accordance with the present invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a diagram of an example of a distributed storage and taskprocessing in accordance with the present invention;

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 5 is a logic diagram of an example of a method for outbound DSTprocessing in accordance with the present invention;

FIG. 6 is a schematic block diagram of an embodiment of a dispersederror encoding in accordance with the present invention;

FIG. 7 is a diagram of an example of a segment processing of thedispersed error encoding in accordance with the present invention;

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding in accordance with thepresent invention;

FIG. 9 is a diagram of an example of grouping selection processing ofthe outbound DST processing in accordance with the present invention;

FIG. 10 is a diagram of an example of converting data into slice groupsin accordance with the present invention;

FIG. 11 is a schematic block diagram of an embodiment of a DST executionunit in accordance with the present invention;

FIG. 12 is a schematic block diagram of an example of operation of a DSTexecution unit in accordance with the present invention;

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 14 is a logic diagram of an example of a method for inbound DSTprocessing in accordance with the present invention;

FIG. 15 is a diagram of an example of de-grouping selection processingof the inbound DST processing in accordance with the present invention;

FIG. 16 is a schematic block diagram of an embodiment of a dispersederror decoding in accordance with the present invention;

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of the dispersed error decoding in accordance with thepresent invention;

FIG. 18 is a diagram of an example of a de-segment processing of thedispersed error decoding in accordance with the present invention;

FIG. 19 is a diagram of an example of converting slice groups into datain accordance with the present invention;

FIG. 20 is a diagram of an example of a distributed storage within thedistributed computing system in accordance with the present invention;

FIG. 21 is a schematic block diagram of an example of operation ofoutbound distributed storage and/or task (DST) processing for storingdata in accordance with the present invention;

FIG. 22 is a schematic block diagram of an example of a dispersed errorencoding for the example of FIG. 21 in accordance with the presentinvention;

FIG. 23 is a diagram of an example of converting data into pillar slicegroups for storage in accordance with the present invention;

FIG. 24 is a schematic block diagram of an example of a storageoperation of a DST execution unit in accordance with the presentinvention;

FIG. 25 is a schematic block diagram of an example of operation ofinbound distributed storage and/or task (DST) processing for retrievingdispersed error encoded data in accordance with the present invention;

FIG. 26 is a schematic block diagram of an example of a dispersed errordecoding for the example of FIG. 25 in accordance with the presentinvention;

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing a plurality ofdata and a plurality of task codes in accordance with the presentinvention;

FIG. 28 is a schematic block diagram of an example of the distributedcomputing system performing tasks on stored data in accordance with thepresent invention;

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module facilitating the example of FIG. 28 in accordancewith the present invention;

FIG. 30 is a diagram of a specific example of the distributed computingsystem performing tasks on stored data in accordance with the presentinvention;

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30 in accordance with the presentinvention;

FIG. 32 is a diagram of an example of DST allocation information for theexample of FIG. 30 in accordance with the present invention;

FIGS. 33-38 are schematic block diagrams of the DSTN module performingthe example of FIG. 30 in accordance with the present invention;

FIG. 39 is a diagram of an example of combining result information intofinal results for the example of FIG. 30 in accordance with the presentinvention;

FIG. 40A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 40B is a flowchart illustrating an example of prioritizingrebuilding data in accordance with the present invention;

FIG. 41A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 41B is a flowchart illustrating an example of prioritizing readingdata in accordance with the present invention;

FIG. 42A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 42B is a flowchart illustrating an example of prioritizing storingdata in accordance with the present invention;

FIG. 43A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 43B is a flowchart illustrating an example of prioritizingdistributed computing tasks in accordance with the present invention;

FIG. 44A is a schematic block diagram of an embodiment of a dispersedstorage network in accordance with the present invention;

FIG. 44B is a flowchart illustrating an example of assigning storageresources in accordance with the present invention;

FIGS. 45A, 45B, and 45G are schematic block diagrams of otherembodiments of a dispersed storage network (DSN) illustrating examplesof storing data in accordance with the present invention;

FIGS. 45C, 45D, 45E, and 45F are timing diagrams illustrating examplesof establishing response time periods in accordance with the presentinvention;

FIG. 45H is a flowchart illustrating an example of storing data inaccordance with the present invention;

FIG. 46A is a schematic block diagram of another embodiment of adispersed storage network in accordance with the present invention;

FIG. 46B is a flowchart illustrating another example of prioritizingrebuilding data in accordance with the present invention;

FIG. 47A is a schematic block diagram of an embodiment of a set ofstorage units in accordance with the present invention;

FIG. 47B is a diagram illustrating an example of a structure of astorage information table in accordance with the present invention;

FIG. 47C is a flowchart illustrating an example of migrating dataformats in accordance with the present invention;

FIGS. 48A-C are diagrams illustrating examples of a series of steps forupdating a dispersed hierarchical index structure in accordance with thepresent invention;

FIG. 48D is a flowchart illustrating an example of migrating nodes of adispersed hierarchical index to a new data format in accordance with thepresent invention;

FIG. 49A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 49B is a flowchart illustrating an example of updating a storageformat in accordance with the present invention;

FIG. 50A is a schematic block diagram of another embodiment of adispersed storage network in accordance with the present invention; and

FIG. 50B is a flowchart illustrating an example of converting a storageformat type in accordance with the present invention

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system 10 that includes a user device 12 and/or a user device14, a distributed storage and/or task (DST) processing unit 16, adistributed storage and/or task network (DSTN) managing unit 18, a DSTintegrity processing unit 20, and a distributed storage and/or tasknetwork (DSTN) module 22. The components of the distributed computingsystem 10 are coupled via a network 24, which may include one or morewireless and/or wire lined communication systems; one or more privateintranet systems and/or public internet systems; and/or one or morelocal area networks (LAN) and/or wide area networks (WAN).

The DSTN module 22 includes a plurality of distributed storage and/ortask (DST) execution units 36 that may be located at geographicallydifferent sites (e.g., one in Chicago, one in Milwaukee, etc.). Each ofthe DST execution units is operable to store dispersed error encodeddata and/or to execute, in a distributed manner, one or more tasks ondata. The tasks may be a simple function (e.g., a mathematical function,a logic function, an identify function, a find function, a search enginefunction, a replace function, etc.), a complex function (e.g.,compression, human and/or computer language translation, text-to-voiceconversion, voice-to-text conversion, etc.), multiple simple and/orcomplex functions, one or more algorithms, one or more applications,etc.

Each of the user devices 12-14, the DST processing unit 16, the DSTNmanaging unit 18, and the DST integrity processing unit 20 include acomputing core 26 and may be a portable computing device and/or a fixedcomputing device. A portable computing device may be a social networkingdevice, a gaming device, a cell phone, a smart phone, a personal digitalassistant, a digital music player, a digital video player, a laptopcomputer, a handheld computer, a tablet, a video game controller, and/orany other portable device that includes a computing core. A fixedcomputing device may be a personal computer (PC), a computer server, acable set-top box, a satellite receiver, a television set, a printer, afax machine, home entertainment equipment, a video game console, and/orany type of home or office computing equipment. User device 12 and DSTprocessing unit 16 are configured to include a DST client module 34.

With respect to interfaces, each interface 30, 32, and 33 includessoftware and/or hardware to support one or more communication links viathe network 24 indirectly and/or directly. For example, interfaces 30support a communication link (e.g., wired, wireless, direct, via a LAN,via the network 24, etc.) between user device 14 and the DST processingunit 16. As another example, interface 32 supports communication links(e.g., a wired connection, a wireless connection, a LAN connection,and/or any other type of connection to/from the network 24) between userdevice 12 and the DSTN module 22 and between the DST processing unit 16and the DSTN module 22. As yet another example, interface 33 supports acommunication link for each of the DSTN managing unit 18 and DSTintegrity processing unit 20 to the network 24.

The distributed computing system 10 is operable to support dispersedstorage (DS) error encoded data storage and retrieval, to supportdistributed task processing on received data, and/or to supportdistributed task processing on stored data. In general and with respectto DS error encoded data storage and retrieval, the distributedcomputing system 10 supports three primary operations: storagemanagement, data storage and retrieval (an example of which will bediscussed with reference to FIGS. 20-26), and data storage integrityverification. In accordance with these three primary functions, data canbe encoded, distributedly stored in physically different locations, andsubsequently retrieved in a reliable and secure manner. Such a system istolerant of a significant number of failures (e.g., up to a failurelevel, which may be greater than or equal to a pillar width minus adecode threshold minus one) that may result from individual storagedevice failures and/or network equipment failures without loss of dataand without the need for a redundant or backup copy. Further, the systemallows the data to be stored for an indefinite period of time withoutdata loss and does so in a secure manner (e.g., the system is veryresistant to attempts at hacking the data).

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has data 40 to store in the DSTN module22, it sends the data 40 to the DST processing unit 16 via its interface30. The interface 30 functions to mimic a conventional operating system(OS) file system interface (e.g., network file system (NFS), flash filesystem (FFS), disk file system (DFS), file transfer protocol (FTP),web-based distributed authoring and versioning (WebDAV), etc.) and/or ablock memory interface (e.g., small computer system interface (SCSI),internet small computer system interface (iSCSI), etc.). In addition,the interface 30 may attach a user identification code (ID) to the data40.

To support storage management, the DSTN managing unit 18 performs DSmanagement services. One such DS management service includes the DSTNmanaging unit 18 establishing distributed data storage parameters (e.g.,vault creation, distributed storage parameters, security parameters,billing information, user profile information, etc.) for a user device12-14 individually or as part of a group of user devices. For example,the DSTN managing unit 18 coordinates creation of a vault (e.g., avirtual memory block) within memory of the DSTN module 22 for a userdevice, a group of devices, or for public access and establishes pervault dispersed storage (DS) error encoding parameters for a vault. TheDSTN managing unit 18 may facilitate storage of DS error encodingparameters for each vault of a plurality of vaults by updating registryinformation for the distributed computing system 10. The facilitatingincludes storing updated registry information in one or more of the DSTNmodule 22, the user device 12, the DST processing unit 16, and the DSTintegrity processing unit 20.

The DS error encoding parameters (e.g. or dispersed storage error codingparameters) include data segmenting information (e.g., how many segmentsdata (e.g., a file, a group of files, a data block, etc.) is dividedinto), segment security information (e.g., per segment encryption,compression, integrity checksum, etc.), error coding information (e.g.,pillar width, decode threshold, read threshold, write threshold, etc.),slicing information (e.g., the number of encoded data slices that willbe created for each data segment); and slice security information (e.g.,per encoded data slice encryption, compression, integrity checksum,etc.).

The DSTN managing module 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSTN module 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSTN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSTN managing unit 18 tracks the number of times a useraccesses a private vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSTNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

Another DS management service includes the DSTN managing unit 18performing network operations, network administration, and/or networkmaintenance. Network operations includes authenticating user dataallocation requests (e.g., read and/or write requests), managingcreation of vaults, establishing authentication credentials for userdevices, adding/deleting components (e.g., user devices, DST executionunits, and/or DST processing units) from the distributed computingsystem 10, and/or establishing authentication credentials for DSTexecution units 36. Network administration includes monitoring devicesand/or units for failures, maintaining vault information, determiningdevice and/or unit activation status, determining device and/or unitloading, and/or determining any other system level operation thataffects the performance level of the system 10. Network maintenanceincludes facilitating replacing, upgrading, repairing, and/or expandinga device and/or unit of the system 10.

To support data storage integrity verification within the distributedcomputing system 10, the DST integrity processing unit 20 performsrebuilding of ‘bad’ or missing encoded data slices. At a high level, theDST integrity processing unit 20 performs rebuilding by periodicallyattempting to retrieve/list encoded data slices, and/or slice names ofthe encoded data slices, from the DSTN module 22. For retrieved encodedslices, they are checked for errors due to data corruption, outdatedversion, etc. If a slice includes an error, it is flagged as a ‘bad’slice. For encoded data slices that were not received and/or not listed,they are flagged as missing slices. Bad and/or missing slices aresubsequently rebuilt using other retrieved encoded data slices that aredeemed to be good slices to produce rebuilt slices. The rebuilt slicesare stored in memory of the DSTN module 22. Note that the DST integrityprocessing unit 20 may be a separate unit as shown, it may be includedin the DSTN module 22, it may be included in the DST processing unit 16,and/or distributed among the DST execution units 36.

To support distributed task processing on received data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task processing) management and DST execution on received data(an example of which will be discussed with reference to FIGS. 3-19).With respect to the storage portion of the DST management, the DSTNmanaging unit 18 functions as previously described. With respect to thetasking processing of the DST management, the DSTN managing unit 18performs distributed task processing (DTP) management services. One suchDTP management service includes the DSTN managing unit 18 establishingDTP parameters (e.g., user-vault affiliation information, billinginformation, user-task information, etc.) for a user device 12-14individually or as part of a group of user devices.

Another DTP management service includes the DSTN managing unit 18performing DTP network operations, network administration (which isessentially the same as described above), and/or network maintenance(which is essentially the same as described above). Network operationsinclude, but are not limited to, authenticating user task processingrequests (e.g., valid request, valid user, etc.), authenticating resultsand/or partial results, establishing DTP authentication credentials foruser devices, adding/deleting components (e.g., user devices, DSTexecution units, and/or DST processing units) from the distributedcomputing system, and/or establishing DTP authentication credentials forDST execution units.

To support distributed task processing on stored data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task) management and DST execution on stored data. With respectto the DST execution on stored data, if the second type of user device14 has a task request 38 for execution by the DSTN module 22, it sendsthe task request 38 to the DST processing unit 16 via its interface 30.An example of DST execution on stored data will be discussed in greaterdetail with reference to FIGS. 27-39. With respect to the DSTmanagement, it is substantially similar to the DST management to supportdistributed task processing on received data.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (TO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSTN interface module 76.

The DSTN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). TheDSTN interface module 76 and/or the network interface module 70 mayfunction as the interface 30 of the user device 14 of FIG. 1. Furthernote that the IO device interface module 62 and/or the memory interfacemodules may be collectively or individually referred to as IO ports.

FIG. 3 is a diagram of an example of the distributed computing systemperforming a distributed storage and task processing operation. Thedistributed computing system includes a DST (distributed storage and/ortask) client module 34 (which may be in user device 14 and/or in DSTprocessing unit 16 of FIG. 1), a network 24, a plurality of DSTexecution units 1-n that includes two or more DST execution units 36 ofFIG. 1 (which form at least a portion of DSTN module 22 of FIG. 1), aDST managing module (not shown), and a DST integrity verification module(not shown). The DST client module 34 includes an outbound DSTprocessing section 80 and an inbound DST processing section 82. Each ofthe DST execution units 1-n includes a controller 86, a processingmodule 84, memory 88, a DT (distributed task) execution module 90, and aDST client module 34.

In an example of operation, the DST client module 34 receives data 92and one or more tasks 94 to be performed upon the data 92. The data 92may be of any size and of any content, where, due to the size (e.g.,greater than a few Terabytes), the content (e.g., secure data, etc.),and/or task(s) (e.g., MIPS intensive), distributed processing of thetask(s) on the data is desired. For example, the data 92 may be one ormore digital books, a copy of a company's emails, a large-scale Internetsearch, a video security file, one or more entertainment video files(e.g., television programs, movies, etc.), data files, and/or any otherlarge amount of data (e.g., greater than a few Terabytes).

Within the DST client module 34, the outbound DST processing section 80receives the data 92 and the task(s) 94. The outbound DST processingsection 80 processes the data 92 to produce slice groupings 96. As anexample of such processing, the outbound DST processing section 80partitions the data 92 into a plurality of data partitions. For eachdata partition, the outbound DST processing section 80 dispersed storage(DS) error encodes the data partition to produce encoded data slices andgroups the encoded data slices into a slice grouping 96. In addition,the outbound DST processing section 80 partitions the task 94 intopartial tasks 98, where the number of partial tasks 98 may correspond tothe number of slice groupings 96.

The outbound DST processing section 80 then sends, via the network 24,the slice groupings 96 and the partial tasks 98 to the DST executionunits 1-n of the DSTN module 22 of FIG. 1. For example, the outbound DSTprocessing section 80 sends slice group 1 and partial task 1 to DSTexecution unit 1. As another example, the outbound DST processingsection 80 sends slice group #n and partial task #n to DST executionunit #n.

Each DST execution unit performs its partial task 98 upon its slicegroup 96 to produce partial results 102. For example, DST execution unit#1 performs partial task #1 on slice group #1 to produce a partialresult #1, for results. As a more specific example, slice group #1corresponds to a data partition of a series of digital books and thepartial task #1 corresponds to searching for specific phrases, recordingwhere the phrase is found, and establishing a phrase count. In this morespecific example, the partial result #1 includes information as to wherethe phrase was found and includes the phrase count.

Upon completion of generating their respective partial results 102, theDST execution units send, via the network 24, their partial results 102to the inbound DST processing section 82 of the DST client module 34.The inbound DST processing section 82 processes the received partialresults 102 to produce a result 104. Continuing with the specificexample of the preceding paragraph, the inbound DST processing section82 combines the phrase count from each of the DST execution units 36 toproduce a total phrase count. In addition, the inbound DST processingsection 82 combines the ‘where the phrase was found’ information fromeach of the DST execution units 36 within their respective datapartitions to produce ‘where the phrase was found’ information for theseries of digital books.

In another example of operation, the DST client module 34 requestsretrieval of stored data within the memory of the DST execution units 36(e.g., memory of the DSTN module). In this example, the task 94 isretrieve data stored in the memory of the DSTN module. Accordingly, theoutbound DST processing section 80 converts the task 94 into a pluralityof partial tasks 98 and sends the partial tasks 98 to the respective DSTexecution units 1-n.

In response to the partial task 98 of retrieving stored data, a DSTexecution unit 36 identifies the corresponding encoded data slices 100and retrieves them. For example, DST execution unit #1 receives partialtask #1 and retrieves, in response thereto, retrieved slices #1. The DSTexecution units 36 send their respective retrieved slices 100 to theinbound DST processing section 82 via the network 24.

The inbound DST processing section 82 converts the retrieved slices 100into data 92. For example, the inbound DST processing section 82de-groups the retrieved slices 100 to produce encoded slices per datapartition. The inbound DST processing section 82 then DS error decodesthe encoded slices per data partition to produce data partitions. Theinbound DST processing section 82 de-partitions the data partitions torecapture the data 92.

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module 34 FIG. 1 coupled to a DSTN module 22 of a FIG. 1 (e.g., aplurality of n DST execution units 36) via a network 24. The outboundDST processing section 80 includes a data partitioning module 110, adispersed storage (DS) error encoding module 112, a grouping selectormodule 114, a control module 116, and a distributed task control module118.

In an example of operation, the data partitioning module 110 partitionsdata 92 into a plurality of data partitions 120. The number ofpartitions and the size of the partitions may be selected by the controlmodule 116 via control 160 based on the data 92 (e.g., its size, itscontent, etc.), a corresponding task 94 to be performed (e.g., simple,complex, single step, multiple steps, etc.), DS encoding parameters(e.g., pillar width, decode threshold, write threshold, segment securityparameters, slice security parameters, etc.), capabilities of the DSTexecution units 36 (e.g., processing resources, availability ofprocessing recourses, etc.), and/or as may be inputted by a user, systemadministrator, or other operator (human or automated). For example, thedata partitioning module 110 partitions the data 92 (e.g., 100Terabytes) into 100,000 data segments, each being 1 Gigabyte in size.Alternatively, the data partitioning module 110 partitions the data 92into a plurality of data segments, where some of data segments are of adifferent size, are of the same size, or a combination thereof.

The DS error encoding module 112 receives the data partitions 120 in aserial manner, a parallel manner, and/or a combination thereof. For eachdata partition 120, the DS error encoding module 112 DS error encodesthe data partition 120 in accordance with control information 160 fromthe control module 116 to produce encoded data slices 122. The DS errorencoding includes segmenting the data partition into data segments,segment security processing (e.g., encryption, compression,watermarking, integrity check (e.g., CRC), etc.), error encoding,slicing, and/or per slice security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC), etc.). Thecontrol information 160 indicates which steps of the DS error encodingare active for a given data partition and, for active steps, indicatesthe parameters for the step. For example, the control information 160indicates that the error encoding is active and includes error encodingparameters (e.g., pillar width, decode threshold, write threshold, readthreshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 122 of a datapartition into a set of slice groupings 96. The number of slicegroupings corresponds to the number of DST execution units 36 identifiedfor a particular task 94. For example, if five DST execution units 36are identified for the particular task 94, the group selecting modulegroups the encoded slices 122 of a data partition into five slicegroupings 96. The grouping selector module 114 outputs the slicegroupings 96 to the corresponding DST execution units 36 via the network24.

The distributed task control module 118 receives the task 94 andconverts the task 94 into a set of partial tasks 98. For example, thedistributed task control module 118 receives a task to find where in thedata (e.g., a series of books) a phrase occurs and a total count of thephrase usage in the data. In this example, the distributed task controlmodule 118 replicates the task 94 for each DST execution unit 36 toproduce the partial tasks 98. In another example, the distributed taskcontrol module 118 receives a task to find where in the data a firstphrase occurs, where in the data a second phrase occurs, and a totalcount for each phrase usage in the data. In this example, thedistributed task control module 118 generates a first set of partialtasks 98 for finding and counting the first phase and a second set ofpartial tasks for finding and counting the second phrase. Thedistributed task control module 118 sends respective first and/or secondpartial tasks 98 to each DST execution unit 36.

FIG. 5 is a logic diagram of an example of a method for outbounddistributed storage and task (DST) processing that begins at step 126where a DST client module receives data and one or more correspondingtasks. The method continues at step 128 where the DST client moduledetermines a number of DST units to support the task for one or moredata partitions. For example, the DST client module may determine thenumber of DST units to support the task based on the size of the data,the requested task, the content of the data, a predetermined number(e.g., user indicated, system administrator determined, etc.), availableDST units, capability of the DST units, and/or any other factorregarding distributed task processing of the data. The DST client modulemay select the same DST units for each data partition, may selectdifferent DST units for the data partitions, or a combination thereof.

The method continues at step 130 where the DST client module determinesprocessing parameters of the data based on the number of DST unitsselected for distributed task processing. The processing parametersinclude data partitioning information, DS encoding parameters, and/orslice grouping information. The data partitioning information includes anumber of data partitions, size of each data partition, and/ororganization of the data partitions (e.g., number of data blocks in apartition, the size of the data blocks, and arrangement of the datablocks). The DS encoding parameters include segmenting information,segment security information, error encoding information (e.g.,dispersed storage error encoding function parameters including one ormore of pillar width, decode threshold, write threshold, read threshold,generator matrix), slicing information, and/or per slice securityinformation. The slice grouping information includes informationregarding how to arrange the encoded data slices into groups for theselected DST units. As a specific example, if the DST client moduledetermines that five DST units are needed to support the task, then itdetermines that the error encoding parameters include a pillar width offive and a decode threshold of three.

The method continues at step 132 where the DST client module determinestask partitioning information (e.g., how to partition the tasks) basedon the selected DST units and data processing parameters. The dataprocessing parameters include the processing parameters and DST unitcapability information. The DST unit capability information includes thenumber of DT (distributed task) execution units, execution capabilitiesof each DT execution unit (e.g., MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or and the other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.)), and/or any information germane toexecuting one or more tasks.

The method continues at step 134 where the DST client module processesthe data in accordance with the processing parameters to produce slicegroupings. The method continues at step 136 where the DST client modulepartitions the task based on the task partitioning information toproduce a set of partial tasks. The method continues at step 138 wherethe DST client module sends the slice groupings and the correspondingpartial tasks to respective DST units.

FIG. 6 is a schematic block diagram of an embodiment of the dispersedstorage (DS) error encoding module 112 of an outbound distributedstorage and task (DST) processing section. The DS error encoding module112 includes a segment processing module 142, a segment securityprocessing module 144, an error encoding module 146, a slicing module148, and a per slice security processing module 150. Each of thesemodules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receives adata partition 120 from a data partitioning module and receivessegmenting information as the control information 160 from the controlmodule 116. The segmenting information indicates how the segmentprocessing module 142 is to segment the data partition 120. For example,the segmenting information indicates how many rows to segment the databased on a decode threshold of an error encoding scheme, indicates howmany columns to segment the data into based on a number and size of datablocks within the data partition 120, and indicates how many columns toinclude in a data segment 152. The segment processing module 142segments the data 120 into data segments 152 in accordance with thesegmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., cyclic redundancy check(CRC), etc.), and/or any other type of digital security. For example,when the segment security processing module 144 is enabled, it maycompress a data segment 152, encrypt the compressed data segment, andgenerate a CRC value for the encrypted data segment to produce a securedata segment 154. When the segment security processing module 144 is notenabled, it passes the data segments 152 to the error encoding module146 or is bypassed such that the data segments 152 are provided to theerror encoding module 146.

The error encoding module 146 encodes the secure data segments 154 inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters (e.g., also referred to as dispersed storage errorcoding parameters) include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an online coding algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction encodingparameters identify a specific error correction encoding scheme,specifies a pillar width of five, and specifies a decode threshold ofthree. From these parameters, the error encoding module 146 encodes adata segment 154 to produce an encoded data segment 156.

The slicing module 148 slices the encoded data segment 156 in accordancewith the pillar width of the error correction encoding parametersreceived as control information 160. For example, if the pillar width isfive, the slicing module 148 slices an encoded data segment 156 into aset of five encoded data slices. As such, for a plurality of encodeddata segments 156 for a given data partition, the slicing module outputsa plurality of sets of encoded data slices 158.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice 158 based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it compresses anencoded data slice 158, encrypts the compressed encoded data slice, andgenerates a CRC value for the encrypted encoded data slice to produce asecure encoded data slice 122. When the per slice security processingmodule 150 is not enabled, it passes the encoded data slices 158 or isbypassed such that the encoded data slices 158 are the output of the DSerror encoding module 112. Note that the control module 116 may beomitted and each module stores its own parameters.

FIG. 7 is a diagram of an example of a segment processing of a dispersedstorage (DS) error encoding module. In this example, a segmentprocessing module 142 receives a data partition 120 that includes 45data blocks (e.g., d1-d45), receives segmenting information (i.e.,control information 160) from a control module, and segments the datapartition 120 in accordance with the control information 160 to producedata segments 152. Each data block may be of the same size as other datablocks or of a different size. In addition, the size of each data blockmay be a few bytes to megabytes of data. As previously mentioned, thesegmenting information indicates how many rows to segment the datapartition into, indicates how many columns to segment the data partitioninto, and indicates how many columns to include in a data segment.

In this example, the decode threshold of the error encoding scheme isthree; as such the number of rows to divide the data partition into isthree. The number of columns for each row is set to 15, which is basedon the number and size of data blocks. The data blocks of the datapartition are arranged in rows and columns in a sequential order (i.e.,the first row includes the first 15 data blocks; the second row includesthe second 15 data blocks; and the third row includes the last 15 datablocks).

With the data blocks arranged into the desired sequential order, theyare divided into data segments based on the segmenting information. Inthis example, the data partition is divided into 8 data segments; thefirst 7 include 2 columns of three rows and the last includes 1 columnof three rows. Note that the first row of the 8 data segments is insequential order of the first 15 data blocks; the second row of the 8data segments in sequential order of the second 15 data blocks; and thethird row of the 8 data segments in sequential order of the last 15 datablocks. Note that the number of data blocks, the grouping of the datablocks into segments, and size of the data blocks may vary toaccommodate the desired distributed task processing function.

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding processing the data segmentsof FIG. 7. In this example, data segment 1 includes 3 rows with each rowbeing treated as one word for encoding. As such, data segment 1 includesthree words for encoding: word 1 including data blocks d1 and d2, word 2including data blocks d16 and d17, and word 3 including data blocks d31and d32. Each of data segments 2-7 includes three words where each wordincludes two data blocks. Data segment 8 includes three words where eachword includes a single data block (e.g., d15, d30, and d45).

In operation, an error encoding module 146 and a slicing module 148convert each data segment into a set of encoded data slices inaccordance with error correction encoding parameters as controlinformation 160. More specifically, when the error correction encodingparameters indicate a unity matrix Reed-Solomon based encodingalgorithm, 5 pillars, and decode threshold of 3, the first three encodeddata slices of the set of encoded data slices for a data segment aresubstantially similar to the corresponding word of the data segment. Forinstance, when the unity matrix Reed-Solomon based encoding algorithm isapplied to data segment 1, the content of the first encoded data slice(DS1_d1&2) of the first set of encoded data slices (e.g., correspondingto data segment 1) is substantially similar to content of the first word(e.g., d1 & d2); the content of the second encoded data slice(DS1_d16&17) of the first set of encoded data slices is substantiallysimilar to content of the second word (e.g., d16 & d17); and the contentof the third encoded data slice (DS1_d31&32) of the first set of encodeddata slices is substantially similar to content of the third word (e.g.,d31 & d32).

The content of the fourth and fifth encoded data slices (e.g., ES1_(—)1and ES1_(—)2) of the first set of encoded data slices include errorcorrection data based on the first-third words of the first datasegment. With such an encoding and slicing scheme, retrieving any threeof the five encoded data slices allows the data segment to be accuratelyreconstructed.

The encoding and slices of data segments 2-7 yield sets of encoded dataslices similar to the set of encoded data slices of data segment 1. Forinstance, the content of the first encoded data slice (DS2_d3&4) of thesecond set of encoded data slices (e.g., corresponding to data segment2) is substantially similar to content of the first word (e.g., d3 &d4); the content of the second encoded data slice (DS2_d18&19) of thesecond set of encoded data slices is substantially similar to content ofthe second word (e.g., d18 & d19); and the content of the third encodeddata slice (DS2_d33&34) of the second set of encoded data slices issubstantially similar to content of the third word (e.g., d33 & d34).The content of the fourth and fifth encoded data slices (e.g., ES1_(—)1and ES1_(—)2) of the second set of encoded data slices includes errorcorrection data based on the first-third words of the second datasegment.

FIG. 9 is a diagram of an example of grouping selection processing of anoutbound distributed storage and task (DST) processing in accordancewith group selection information as control information 160 from acontrol module. Encoded slices for data partition 122 are grouped inaccordance with the control information 160 to produce slice groupings96. In this example, a grouping selection module 114 organizes theencoded data slices into five slice groupings (e.g., one for each DSTexecution unit of a distributed storage and task network (DSTN) module).As a specific example, the grouping selection module 114 creates a firstslice grouping for a DST execution unit #1, which includes first encodedslices of each of the sets of encoded slices. As such, the first DSTexecution unit receives encoded data slices corresponding to data blocks1-15 (e.g., encoded data slices of contiguous data).

The grouping selection module 114 also creates a second slice groupingfor a DST execution unit #2, which includes second encoded slices ofeach of the sets of encoded slices. As such, the second DST executionunit receives encoded data slices corresponding to data blocks 16-30.The grouping selection module 114 further creates a third slice groupingfor DST execution unit #3, which includes third encoded slices of eachof the sets of encoded slices. As such, the third DST execution unitreceives encoded data slices corresponding to data blocks 31-45.

The grouping selection module 114 creates a fourth slice grouping forDST execution unit #4, which includes fourth encoded slices of each ofthe sets of encoded slices. As such, the fourth DST execution unitreceives encoded data slices corresponding to first error encodinginformation (e.g., encoded data slices of error coding (EC) data). Thegrouping selection module 114 further creates a fifth slice grouping forDST execution unit #5, which includes fifth encoded slices of each ofthe sets of encoded slices. As such, the fifth DST execution unitreceives encoded data slices corresponding to second error encodinginformation.

FIG. 10 is a diagram of an example of converting data 92 into slicegroups that expands on the preceding figures. As shown, the data 92 ispartitioned in accordance with a partitioning function 164 into aplurality of data partitions (1-x, where x is an integer greater than4). Each data partition (or chunkset of data) is encoded and groupedinto slice groupings as previously discussed by an encoding and groupingfunction 166. For a given data partition, the slice groupings are sentto distributed storage and task (DST) execution units. From datapartition to data partition, the ordering of the slice groupings to theDST execution units may vary.

For example, the slice groupings of data partition #1 is sent to the DSTexecution units such that the first DST execution receives first encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a first continuous data chunk of the first data partition(e.g., refer to FIG. 9), a second DST execution receives second encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a second continuous data chunk of the first datapartition, etc.

For the second data partition, the slice groupings may be sent to theDST execution units in a different order than it was done for the firstdata partition. For instance, the first slice grouping of the seconddata partition (e.g., slice group 2_(—)1) is sent to the second DSTexecution unit; the second slice grouping of the second data partition(e.g., slice group 2_(—)2) is sent to the third DST execution unit; thethird slice grouping of the second data partition (e.g., slice group2_(—)3) is sent to the fourth DST execution unit; the fourth slicegrouping of the second data partition (e.g., slice group 2_(—)4, whichincludes first error coding information) is sent to the fifth DSTexecution unit; and the fifth slice grouping of the second datapartition (e.g., slice group 2_(—)5, which includes second error codinginformation) is sent to the first DST execution unit.

The pattern of sending the slice groupings to the set of DST executionunits may vary in a predicted pattern, a random pattern, and/or acombination thereof from data partition to data partition. In addition,from data partition to data partition, the set of DST execution unitsmay change. For example, for the first data partition, DST executionunits 1-5 may be used; for the second data partition, DST executionunits 6-10 may be used; for the third data partition, DST executionunits 3-7 may be used; etc. As is also shown, the task is divided intopartial tasks that are sent to the DST execution units in conjunctionwith the slice groupings of the data partitions.

FIG. 11 is a schematic block diagram of an embodiment of a DST(distributed storage and/or task) execution unit that includes aninterface 169, a controller 86, memory 88, one or more DT (distributedtask) execution modules 90, and a DST client module 34. The memory 88 isof sufficient size to store a significant number of encoded data slices(e.g., thousands of slices to hundreds-of-millions of slices) and mayinclude one or more hard drives and/or one or more solid-state memorydevices (e.g., flash memory, DRAM, etc.).

In an example of storing a slice group, the DST execution modulereceives a slice grouping 96 (e.g., slice group #1) via interface 169.The slice grouping 96 includes, per partition, encoded data slices ofcontiguous data or encoded data slices of error coding (EC) data. Forslice group #1, the DST execution module receives encoded data slices ofcontiguous data for partitions #1 and #x (and potentially others between3 and x) and receives encoded data slices of EC data for partitions #2and #3 (and potentially others between 3 and x). Examples of encodeddata slices of contiguous data and encoded data slices of error coding(EC) data are discussed with reference to FIG. 9. The memory 88 storesthe encoded data slices of slice groupings 96 in accordance with memorycontrol information 174 it receives from the controller 86.

The controller 86 (e.g., a processing module, a CPU, etc.) generates thememory control information 174 based on a partial task(s) 98 anddistributed computing information (e.g., user information (e.g., userID, distributed computing permissions, data access permission, etc.),vault information (e.g., virtual memory assigned to user, user group,temporary storage for task processing, etc.), task validationinformation, etc.). For example, the controller 86 interprets thepartial task(s) 98 in light of the distributed computing information todetermine whether a requestor is authorized to perform the task 98, isauthorized to access the data, and/or is authorized to perform the taskon this particular data. When the requestor is authorized, thecontroller 86 determines, based on the task 98 and/or another input,whether the encoded data slices of the slice grouping 96 are to betemporarily stored or permanently stored. Based on the foregoing, thecontroller 86 generates the memory control information 174 to write theencoded data slices of the slice grouping 96 into the memory 88 and toindicate whether the slice grouping 96 is permanently stored ortemporarily stored.

With the slice grouping 96 stored in the memory 88, the controller 86facilitates execution of the partial task(s) 98. In an example, thecontroller 86 interprets the partial task 98 in light of thecapabilities of the DT execution module(s) 90. The capabilities includeone or more of MIPS capabilities, processing resources (e.g., quantityand capability of microprocessors, CPUs, digital signal processors,co-processor, microcontrollers, arithmetic logic circuitry, and/or anyother analog and/or digital processing circuitry), availability of theprocessing resources, etc. If the controller 86 determines that the DTexecution module(s) 90 have sufficient capabilities, it generates taskcontrol information 176.

The task control information 176 may be a generic instruction (e.g.,perform the task on the stored slice grouping) or a series ofoperational codes. In the former instance, the DT execution module 90includes a co-processor function specifically configured (fixed orprogrammed) to perform the desired task 98. In the latter instance, theDT execution module 90 includes a general processor topology where thecontroller stores an algorithm corresponding to the particular task 98.In this instance, the controller 86 provides the operational codes(e.g., assembly language, source code of a programming language, objectcode, etc.) of the algorithm to the DT execution module 90 forexecution.

Depending on the nature of the task 98, the DT execution module 90 maygenerate intermediate partial results 102 that are stored in the memory88 or in a cache memory (not shown) within the DT execution module 90.In either case, when the DT execution module 90 completes execution ofthe partial task 98, it outputs one or more partial results 102. Thepartial results 102 may also be stored in memory 88.

If, when the controller 86 is interpreting whether capabilities of theDT execution module(s) 90 can support the partial task 98, thecontroller 86 determines that the DT execution module(s) 90 cannotadequately support the task 98 (e.g., does not have the right resources,does not have sufficient available resources, available resources wouldbe too slow, etc.), it then determines whether the partial task 98should be fully offloaded or partially offloaded.

If the controller 86 determines that the partial task 98 should be fullyoffloaded, it generates DST control information 178 and provides it tothe DST client module 34. The DST control information 178 includes thepartial task 98, memory storage information regarding the slice grouping96, and distribution instructions. The distribution instructionsinstruct the DST client module 34 to divide the partial task 98 intosub-partial tasks 172, to divide the slice grouping 96 into sub-slicegroupings 170, and identify other DST execution units. The DST clientmodule 34 functions in a similar manner as the DST client module 34 ofFIGS. 3-10 to produce the sub-partial tasks 172 and the sub-slicegroupings 170 in accordance with the distribution instructions.

The DST client module 34 receives DST feedback 168 (e.g., sub-partialresults), via the interface 169, from the DST execution units to whichthe task was offloaded. The DST client module 34 provides thesub-partial results to the DST execution unit, which processes thesub-partial results to produce the partial result(s) 102.

If the controller 86 determines that the partial task 98 should bepartially offloaded, it determines what portion of the task 98 and/orslice grouping 96 should be processed locally and what should beoffloaded. For the portion that is being locally processed, thecontroller 86 generates task control information 176 as previouslydiscussed. For the portion that is being offloaded, the controller 86generates DST control information 178 as previously discussed.

When the DST client module 34 receives DST feedback 168 (e.g.,sub-partial results) from the DST executions units to which a portion ofthe task was offloaded, it provides the sub-partial results to the DTexecution module 90. The DT execution module 90 processes thesub-partial results with the sub-partial results it created to producethe partial result(s) 102.

The memory 88 may be further utilized to retrieve one or more of storedslices 100, stored results 104, partial results 102 when the DTexecution module 90 stores partial results 102 and/or results 104 andthe memory 88. For example, when the partial task 98 includes aretrieval request, the controller 86 outputs the memory control 174 tothe memory 88 to facilitate retrieval of slices 100 and/or results 104.

FIG. 12 is a schematic block diagram of an example of operation of adistributed storage and task (DST) execution unit storing encoded dataslices and executing a task thereon. To store the encoded data slices ofa partition 1 of slice grouping 1, a controller 86 generates writecommands as memory control information 174 such that the encoded slicesare stored in desired locations (e.g., permanent or temporary) withinmemory 88.

Once the encoded slices are stored, the controller 86 provides taskcontrol information 176 to a distributed task (DT) execution module 90.As a first step executing the task in accordance with the task controlinformation 176, the DT execution module 90 retrieves the encoded slicesfrom memory 88. The DT execution module 90 then reconstructs contiguousdata blocks of a data partition. As shown for this example,reconstructed contiguous data blocks of data partition 1 include datablocks 1-15 (e.g., d1-d15).

With the contiguous data blocks reconstructed, the DT execution module90 performs the task on the reconstructed contiguous data blocks. Forexample, the task may be to search the reconstructed contiguous datablocks for a particular word or phrase, identify where in thereconstructed contiguous data blocks the particular word or phraseoccurred, and/or count the occurrences of the particular word or phraseon the reconstructed contiguous data blocks. The DST execution unitcontinues in a similar manner for the encoded data slices of otherpartitions in slice grouping 1. Note that with using the unity matrixerror encoding scheme previously discussed, if the encoded data slicesof contiguous data are uncorrupted, the decoding of them is a relativelystraightforward process of extracting the data.

If, however, an encoded data slice of contiguous data is corrupted (ormissing), it can be rebuilt by accessing other DST execution units thatare storing the other encoded data slices of the set of encoded dataslices of the corrupted encoded data slice. In this instance, the DSTexecution unit having the corrupted encoded data slices retrieves atleast three encoded data slices (of contiguous data and of error codingdata) in the set from the other DST execution units (recall for thisexample, the pillar width is 5 and the decode threshold is 3). The DSTexecution unit decodes the retrieved data slices using the DS errorencoding parameters to recapture the corresponding data segment. The DSTexecution unit then re-encodes the data segment using the DS errorencoding parameters to rebuild the corrupted encoded data slice. Oncethe encoded data slice is rebuilt, the DST execution unit functions aspreviously described.

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing section 82 of a DSTclient module coupled to DST execution units of a distributed storageand task network (DSTN) module via a network 24. The inbound DSTprocessing section 82 includes a de-grouping module 180, a DS (dispersedstorage) error decoding module 182, a data de-partitioning module 184, acontrol module 186, and a distributed task control module 188. Note thatthe control module 186 and/or the distributed task control module 188may be separate modules from corresponding ones of outbound DSTprocessing section or may be the same modules.

In an example of operation, the DST execution units have completedexecution of corresponding partial tasks on the corresponding slicegroupings to produce partial results 102. The inbound DST processingsection 82 receives the partial results 102 via the distributed taskcontrol module 188. The inbound DST processing section 82 then processesthe partial results 102 to produce a final result, or results 104. Forexample, if the task was to find a specific word or phrase within data,the partial results 102 indicate where in each of the prescribedportions of the data the corresponding DST execution units found thespecific word or phrase. The distributed task control module 188combines the individual partial results 102 for the correspondingportions of the data into a final result 104 for the data as a whole.

In another example of operation, the inbound DST processing section 82is retrieving stored data from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices 100 corresponding to the data retrieval requests. The de-groupingmodule 180 receives retrieved slices 100 and de-groups them to produceencoded data slices per data partition 122. The DS error decoding module182 decodes, in accordance with DS error encoding parameters, theencoded data slices per data partition 122 to produce data partitions120.

The data de-partitioning module 184 combines the data partitions 120into the data 92. The control module 186 controls the conversion ofretrieve slices 100 into the data 92 using control signals 190 to eachof the modules. For instance, the control module 186 providesde-grouping information to the de-grouping module 180, provides the DSerror encoding parameters to the DS error decoding module 182, andprovides de-partitioning information to the data de-partitioning module184.

FIG. 14 is a logic diagram of an example of a method that is executableby distributed storage and task (DST) client module regarding inboundDST processing. The method begins at step 194 where the DST clientmodule receives partial results. The method continues at step 196 wherethe DST client module retrieves the task corresponding to the partialresults. For example, the partial results include header informationthat identifies the requesting entity, which correlates to the requestedtask.

The method continues at step 198 where the DST client module determinesresult processing information based on the task. For example, if thetask were to identify a particular word or phrase within the data, theresult processing information would indicate to aggregate the partialresults for the corresponding portions of the data to produce the finalresult. As another example, if the task were to count the occurrences ofa particular word or phrase within the data, results of processing theinformation would indicate to add the partial results to produce thefinal results. The method continues at step 200 where the DST clientmodule processes the partial results in accordance with the resultprocessing information to produce the final result or results.

FIG. 15 is a diagram of an example of de-grouping selection processingof an inbound distributed storage and task (DST) processing section of aDST client module. In general, this is an inverse process of thegrouping module of the outbound DST processing section of FIG. 9.Accordingly, for each data partition (e.g., partition #1), thede-grouping module retrieves the corresponding slice grouping from theDST execution units (EU) (e.g., DST 1-5).

As shown, DST execution unit #1 provides a first slice grouping, whichincludes the first encoded slices of each of the sets of encoded slices(e.g., encoded data slices of contiguous data of data blocks 1-15); DSTexecution unit #2 provides a second slice grouping, which includes thesecond encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 16-30); DSTexecution unit #3 provides a third slice grouping, which includes thethird encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 31-45); DSTexecution unit #4 provides a fourth slice grouping, which includes thefourth encoded slices of each of the sets of encoded slices (e.g., firstencoded data slices of error coding (EC) data); and DST execution unit#5 provides a fifth slice grouping, which includes the fifth encodedslices of each of the sets of encoded slices (e.g., first encoded dataslices of error coding (EC) data).

The de-grouping module de-groups the slice groupings (e.g., receivedslices 100) using a de-grouping selector 180 controlled by a controlsignal 190 as shown in the example to produce a plurality of sets ofencoded data slices (e.g., retrieved slices for a partition into sets ofslices 122). Each set corresponding to a data segment of the datapartition.

FIG. 16 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, a de-segmenting processing module 210, and acontrol module 186.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186, unsecures eachencoded data slice 122 based on slice de-security information receivedas control information 190 (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received from thecontrol module 186. The slice security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRCverification, etc.), and/or any other type of digital security. Forexample, when the inverse per slice security processing module 202 isenabled, it verifies integrity information (e.g., a CRC value) of eachencoded data slice 122, it decrypts each verified encoded data slice,and decompresses each decrypted encoded data slice to produce sliceencoded data 158. When the inverse per slice security processing module202 is not enabled, it passes the encoded data slices 122 as the slicedencoded data 158 or is bypassed such that the retrieved encoded dataslices 122 are provided as the sliced encoded data 158.

The de-slicing module 204 de-slices the sliced encoded data 158 intoencoded data segments 156 in accordance with a pillar width of the errorcorrection encoding parameters received as control information 190 fromthe control module 186. For example, if the pillar width is five, thede-slicing module 204 de-slices a set of five encoded data slices intoan encoded data segment 156. The error decoding module 206 decodes theencoded data segments 156 in accordance with error correction decodingparameters received as control information 190 from the control module186 to produce secure data segments 154. The error correction decodingparameters include identifying an error correction encoding scheme(e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction decoding parameters identify a specific errorcorrection encoding scheme, specify a pillar width of five, and specifya decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments 154 based onsegment security information received as control information 190 fromthe control module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module 208 isenabled, it verifies integrity information (e.g., a CRC value) of eachsecure data segment 154, it decrypts each verified secured data segment,and decompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 154 as the data segment152 or is bypassed.

The de-segment processing module 210 receives the data segments 152 andreceives de-segmenting information as control information 190 from thecontrol module 186. The de-segmenting information indicates how thede-segment processing module 210 is to de-segment the data segments 152into a data partition 120. For example, the de-segmenting informationindicates how the rows and columns of data segments are to be rearrangedto yield the data partition 120.

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of a dispersed error decoding module. A de-slicing module 204receives at least a decode threshold number of encoded data slices 158for each data segment in accordance with control information 190 andprovides encoded data 156. In this example, a decode threshold is three.As such, each set of encoded data slices 158 is shown to have threeencoded data slices per data segment. The de-slicing module 204 mayreceive three encoded data slices per data segment because an associateddistributed storage and task (DST) client module requested retrievingonly three encoded data slices per segment or selected three of theretrieved encoded data slices per data segment. As shown, which is basedon the unity matrix encoding previously discussed with reference to FIG.8, an encoded data slice may be a data-based encoded data slice (e.g.,DS1_d1&d2) or an error code based encoded data slice (e.g., ES3_(—)1).

An error decoding module 206 decodes the encoded data 156 of each datasegment in accordance with the error correction decoding parameters ofcontrol information 190 to produce secured segments 154. In thisexample, data segment 1 includes 3 rows with each row being treated asone word for encoding. As such, data segment 1 includes three words:word 1 including data blocks d1 and d2, word 2 including data blocks d16and d17, and word 3 including data blocks d31 and d32. Each of datasegments 2-7 includes three words where each word includes two datablocks. Data segment 8 includes three words where each word includes asingle data block (e.g., d15, d30, and d45).

FIG. 18 is a diagram of an example of a de-segment processing of aninbound distributed storage and task (DST) processing. In this example,a de-segment processing module 210 receives data segments 152 (e.g.,1-8) and rearranges the data blocks of the data segments into rows andcolumns in accordance with de-segmenting information of controlinformation 190 to produce a data partition 120. Note that the number ofrows is based on the decode threshold (e.g., 3 in this specific example)and the number of columns is based on the number and size of the datablocks.

The de-segmenting module 210 converts the rows and columns of datablocks into the data partition 120. Note that each data block may be ofthe same size as other data blocks or of a different size. In addition,the size of each data block may be a few bytes to megabytes of data.

FIG. 19 is a diagram of an example of converting slice groups into data92 within an inbound distributed storage and task (DST) processingsection. As shown, the data 92 is reconstructed from a plurality of datapartitions (1-x, where x is an integer greater than 4). Each datapartition (or chunk set of data) is decoded and re-grouped using ade-grouping and decoding function 212 and a de-partition function 214from slice groupings as previously discussed. For a given datapartition, the slice groupings (e.g., at least a decode threshold perdata segment of encoded data slices) are received from DST executionunits. From data partition to data partition, the ordering of the slicegroupings received from the DST execution units may vary as discussedwith reference to FIG. 10.

FIG. 20 is a diagram of an example of a distributed storage and/orretrieval within the distributed computing system. The distributedcomputing system includes a plurality of distributed storage and/or task(DST) processing client modules 34 (one shown) coupled to a distributedstorage and/or task processing network (DSTN) module, or multiple DSTNmodules, via a network 24. The DST client module 34 includes an outboundDST processing section 80 and an inbound DST processing section 82. TheDSTN module includes a plurality of DST execution units. Each DSTexecution unit includes a controller 86, memory 88, one or moredistributed task (DT) execution modules 90, and a DST client module 34.

In an example of data storage, the DST client module 34 has data 92 thatit desires to store in the DSTN module. The data 92 may be a file (e.g.,video, audio, text, graphics, etc.), a data object, a data block, anupdate to a file, an update to a data block, etc. In this instance, theoutbound DST processing module 80 converts the data 92 into encoded dataslices 216 as will be further described with reference to FIGS. 21-23.The outbound DST processing module 80 sends, via the network 24, to theDST execution units for storage as further described with reference toFIG. 24.

In an example of data retrieval, the DST client module 34 issues aretrieve request to the DST execution units for the desired data 92. Theretrieve request may address each DST executions units storing encodeddata slices of the desired data, address a decode threshold number ofDST execution units, address a read threshold number of DST executionunits, or address some other number of DST execution units. In responseto the request, each addressed DST execution unit retrieves its encodeddata slices 100 of the desired data and sends them to the inbound DSTprocessing section 82, via the network 24.

When, for each data segment, the inbound DST processing section 82receives at least a decode threshold number of encoded data slices 100,it converts the encoded data slices 100 into a data segment. The inboundDST processing section 82 aggregates the data segments to produce theretrieved data 92.

FIG. 21 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module coupled to a distributed storage and task network (DSTN)module (e.g., a plurality of DST execution units) via a network 24. Theoutbound DST processing section 80 includes a data partitioning module110, a dispersed storage (DS) error encoding module 112, a groupingselector module 114, a control module 116, and a distributed taskcontrol module 118.

In an example of operation, the data partitioning module 110 isby-passed such that data 92 is provided directly to the DS errorencoding module 112. The control module 116 coordinates the by-passingof the data partitioning module 110 by outputting a bypass 220 messageto the data partitioning module 110.

The DS error encoding module 112 receives the data 92 in a serialmanner, a parallel manner, and/or a combination thereof. The DS errorencoding module 112 DS error encodes the data in accordance with controlinformation 160 from the control module 116 to produce encoded dataslices 218. The DS error encoding includes segmenting the data 92 intodata segments, segment security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC, etc.)), errorencoding, slicing, and/or per slice security processing (e.g.,encryption, compression, watermarking, integrity check (e.g., CRC,etc.)). The control information 160 indicates which steps of the DSerror encoding are active for the data 92 and, for active steps,indicates the parameters for the step. For example, the controlinformation 160 indicates that the error encoding is active and includeserror encoding parameters (e.g., pillar width, decode threshold, writethreshold, read threshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 218 of thedata segments into pillars of slices 216. The number of pillarscorresponds to the pillar width of the DS error encoding parameters. Inthis example, the distributed task control module 118 facilitates thestorage request.

FIG. 22 is a schematic block diagram of an example of a dispersedstorage (DS) error encoding module 112 for the example of FIG. 21. TheDS error encoding module 112 includes a segment processing module 142, asegment security processing module 144, an error encoding module 146, aslicing module 148, and a per slice security processing module 150. Eachof these modules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receivesdata 92 and receives segmenting information as control information 160from the control module 116. The segmenting information indicates howthe segment processing module is to segment the data. For example, thesegmenting information indicates the size of each data segment. Thesegment processing module 142 segments the data 92 into data segments152 in accordance with the segmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., CRC, etc.), and/or anyother type of digital security. For example, when the segment securityprocessing module 144 is enabled, it compresses a data segment 152,encrypts the compressed data segment, and generates a CRC value for theencrypted data segment to produce a secure data segment. When thesegment security processing module 144 is not enabled, it passes thedata segments 152 to the error encoding module 146 or is bypassed suchthat the data segments 152 are provided to the error encoding module146.

The error encoding module 146 encodes the secure data segments inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction encoding parameters identify a specific errorcorrection encoding scheme, specifies a pillar width of five, andspecifies a decode threshold of three. From these parameters, the errorencoding module 146 encodes a data segment to produce an encoded datasegment.

The slicing module 148 slices the encoded data segment in accordancewith a pillar width of the error correction encoding parameters. Forexample, if the pillar width is five, the slicing module slices anencoded data segment into a set of five encoded data slices. As such,for a plurality of data segments, the slicing module 148 outputs aplurality of sets of encoded data slices as shown within encoding andslicing function 222 as described.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it may compress anencoded data slice, encrypt the compressed encoded data slice, andgenerate a CRC value for the encrypted encoded data slice to produce asecure encoded data slice tweaking. When the per slice securityprocessing module 150 is not enabled, it passes the encoded data slicesor is bypassed such that the encoded data slices 218 are the output ofthe DS error encoding module 112.

FIG. 23 is a diagram of an example of converting data 92 into pillarslice groups utilizing encoding, slicing and pillar grouping function224 for storage in memory of a distributed storage and task network(DSTN) module. As previously discussed the data 92 is encoded and slicedinto a plurality of sets of encoded data slices; one set per datasegment. The grouping selection module organizes the sets of encodeddata slices into pillars of data slices. In this example, the DS errorencoding parameters include a pillar width of 5 and a decode thresholdof 3. As such, for each data segment, 5 encoded data slices are created.

The grouping selection module takes the first encoded data slice of eachof the sets and forms a first pillar, which may be sent to the first DSTexecution unit. Similarly, the grouping selection module creates thesecond pillar from the second slices of the sets; the third pillar fromthe third slices of the sets; the fourth pillar from the fourth slicesof the sets; and the fifth pillar from the fifth slices of the set.

FIG. 24 is a schematic block diagram of an embodiment of a distributedstorage and/or task (DST) execution unit that includes an interface 169,a controller 86, memory 88, one or more distributed task (DT) executionmodules 90, and a DST client module 34. A computing core 26 may beutilized to implement the one or more DT execution modules 90 and theDST client module 34. The memory 88 is of sufficient size to store asignificant number of encoded data slices (e.g., thousands of slices tohundreds-of-millions of slices) and may include one or more hard drivesand/or one or more solid-state memory devices (e.g., flash memory, DRAM,etc.).

In an example of storing a pillar of slices 216, the DST execution unitreceives, via interface 169, a pillar of slices 216 (e.g., pillar #1slices). The memory 88 stores the encoded data slices 216 of the pillarof slices in accordance with memory control information 174 it receivesfrom the controller 86. The controller 86 (e.g., a processing module, aCPU, etc.) generates the memory control information 174 based ondistributed storage information (e.g., user information (e.g., user ID,distributed storage permissions, data access permission, etc.), vaultinformation (e.g., virtual memory assigned to user, user group, etc.),etc.). Similarly, when retrieving slices, the DST execution unitreceives, via interface 169, a slice retrieval request. The memory 88retrieves the slice in accordance with memory control information 174 itreceives from the controller 86. The memory 88 outputs the slice 100,via the interface 169, to a requesting entity.

FIG. 25 is a schematic block diagram of an example of operation of aninbound distributed storage and/or task (DST) processing section 82 forretrieving dispersed error encoded data 92. The inbound DST processingsection 82 includes a de-grouping module 180, a dispersed storage (DS)error decoding module 182, a data de-partitioning module 184, a controlmodule 186, and a distributed task control module 188. Note that thecontrol module 186 and/or the distributed task control module 188 may beseparate modules from corresponding ones of an outbound DST processingsection or may be the same modules.

In an example of operation, the inbound DST processing section 82 isretrieving stored data 92 from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices corresponding to data retrieval requests from the distributedtask control module 188. The de-grouping module 180 receives pillars ofslices 100 and de-groups them in accordance with control information 190from the control module 186 to produce sets of encoded data slices 218.The DS error decoding module 182 decodes, in accordance with the DSerror encoding parameters received as control information 190 from thecontrol module 186, each set of encoded data slices 218 to produce datasegments, which are aggregated into retrieved data 92. The datade-partitioning module 184 is by-passed in this operational mode via abypass signal 226 of control information 190 from the control module186.

FIG. 26 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, and a de-segmenting processing module 210. Thedispersed error decoding module 182 is operable to de-slice and decodeencoded slices per data segment 218 utilizing a de-slicing and decodingfunction 228 to produce a plurality of data segments that arede-segmented utilizing a de-segment function 230 to recover data 92.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186 via controlinformation 190, unsecures each encoded data slice 218 based on slicede-security information (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received as controlinformation 190 from the control module 186. The slice de-securityinformation includes data decompression, decryption, de-watermarking,integrity check (e.g., CRC verification, etc.), and/or any other type ofdigital security. For example, when the inverse per slice securityprocessing module 202 is enabled, it verifies integrity information(e.g., a CRC value) of each encoded data slice 218, it decrypts eachverified encoded data slice, and decompresses each decrypted encodeddata slice to produce slice encoded data. When the inverse per slicesecurity processing module 202 is not enabled, it passes the encodeddata slices 218 as the sliced encoded data or is bypassed such that theretrieved encoded data slices 218 are provided as the sliced encodeddata.

The de-slicing module 204 de-slices the sliced encoded data into encodeddata segments in accordance with a pillar width of the error correctionencoding parameters received as control information 190 from a controlmodule 186. For example, if the pillar width is five, the de-slicingmodule de-slices a set of five encoded data slices into an encoded datasegment. Alternatively, the encoded data segment may include just threeencoded data slices (e.g., when the decode threshold is 3).

The error decoding module 206 decodes the encoded data segments inaccordance with error correction decoding parameters received as controlinformation 190 from the control module 186 to produce secure datasegments. The error correction decoding parameters include identifyingan error correction encoding scheme (e.g., forward error correctionalgorithm, a Reed-Solomon based algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction decodingparameters identify a specific error correction encoding scheme, specifya pillar width of five, and specify a decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments based on segmentsecurity information received as control information 190 from thecontrol module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module is enabled,it verifies integrity information (e.g., a CRC value) of each securedata segment, it decrypts each verified secured data segment, anddecompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 152 as the data segmentor is bypassed. The de-segmenting processing module 210 aggregates thedata segments 152 into the data 92 in accordance with controlinformation 190 from the control module 186.

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module that includes aplurality of distributed storage and task (DST) execution units (#1through #n, where, for example, n is an integer greater than or equal tothree). Each of the DST execution units includes a DST client module 34,a controller 86, one or more DT (distributed task) execution modules 90,and memory 88.

In this example, the DSTN module stores, in the memory of the DSTexecution units, a plurality of DS (dispersed storage) encoded data(e.g., 1 through n, where n is an integer greater than or equal to two)and stores a plurality of DS encoded task codes (e.g., 1 through k,where k is an integer greater than or equal to two). The DS encoded datamay be encoded in accordance with one or more examples described withreference to FIGS. 3-19 (e.g., organized in slice groupings) or encodedin accordance with one or more examples described with reference toFIGS. 20-26 (e.g., organized in pillar groups). The data that is encodedinto the DS encoded data may be of any size and/or of any content. Forexample, the data may be one or more digital books, a copy of acompany's emails, a large-scale Internet search, a video security file,one or more entertainment video files (e.g., television programs,movies, etc.), data files, and/or any other large amount of data (e.g.,greater than a few Terabytes).

The tasks that are encoded into the DS encoded task code may be a simplefunction (e.g., a mathematical function, a logic function, an identifyfunction, a find function, a search engine function, a replace function,etc.), a complex function (e.g., compression, human and/or computerlanguage translation, text-to-voice conversion, voice-to-textconversion, etc.), multiple simple and/or complex functions, one or morealgorithms, one or more applications, etc. The tasks may be encoded intothe DS encoded task code in accordance with one or more examplesdescribed with reference to FIGS. 3-19 (e.g., organized in slicegroupings) or encoded in accordance with one or more examples describedwith reference to FIGS. 20-26 (e.g., organized in pillar groups).

In an example of operation, a DST client module of a user device or of aDST processing unit issues a DST request to the DSTN module. The DSTrequest may include a request to retrieve stored data, or a portionthereof, may include a request to store data that is included with theDST request, may include a request to perform one or more tasks onstored data, may include a request to perform one or more tasks on dataincluded with the DST request, etc. In the cases where the DST requestincludes a request to store data or to retrieve data, the client moduleand/or the DSTN module processes the request as previously discussedwith reference to one or more of FIGS. 3-19 (e.g., slice groupings)and/or 20-26 (e.g., pillar groupings). In the case where the DST requestincludes a request to perform one or more tasks on data included withthe DST request, the DST client module and/or the DSTN module processthe DST request as previously discussed with reference to one or more ofFIGS. 3-19.

In the case where the DST request includes a request to perform one ormore tasks on stored data, the DST client module and/or the DSTN moduleprocesses the DST request as will be described with reference to one ormore of FIGS. 28-39. In general, the DST client module identifies dataand one or more tasks for the DSTN module to execute upon the identifieddata. The DST request may be for a one-time execution of the task or foran on-going execution of the task. As an example of the latter, as acompany generates daily emails, the DST request may be to daily searchnew emails for inappropriate content and, if found, record the content,the email sender(s), the email recipient(s), email routing information,notify human resources of the identified email, etc.

FIG. 28 is a schematic block diagram of an example of a distributedcomputing system performing tasks on stored data. In this example, twodistributed storage and task (DST) client modules 1-2 are shown: thefirst may be associated with a user device and the second may beassociated with a DST processing unit or a high priority user device(e.g., high priority clearance user, system administrator, etc.). EachDST client module includes a list of stored data 234 and a list of taskscodes 236. The list of stored data 234 includes one or more entries ofdata identifying information, where each entry identifies data stored inthe DSTN module 22. The data identifying information (e.g., data ID)includes one or more of a data file name, a data file directory listing,DSTN addressing information of the data, a data object identifier, etc.The list of tasks 236 includes one or more entries of task codeidentifying information, when each entry identifies task codes stored inthe DSTN module 22. The task code identifying information (e.g., taskID) includes one or more of a task file name, a task file directorylisting, DSTN addressing information of the task, another type ofidentifier to identify the task, etc.

As shown, the list of data 234 and the list of tasks 236 are eachsmaller in number of entries for the first DST client module than thecorresponding lists of the second DST client module. This may occurbecause the user device associated with the first DST client module hasfewer privileges in the distributed computing system than the deviceassociated with the second DST client module. Alternatively, this mayoccur because the user device associated with the first DST clientmodule serves fewer users than the device associated with the second DSTclient module and is restricted by the distributed computing systemaccordingly. As yet another alternative, this may occur through norestraints by the distributed computing system, it just occurred becausethe operator of the user device associated with the first DST clientmodule has selected fewer data and/or fewer tasks than the operator ofthe device associated with the second DST client module.

In an example of operation, the first DST client module selects one ormore data entries 238 and one or more tasks 240 from its respectivelists (e.g., selected data ID and selected task ID). The first DSTclient module sends its selections to a task distribution module 232.The task distribution module 232 may be within a stand-alone device ofthe distributed computing system, may be within the user device thatcontains the first DST client module, or may be within the DSTN module22.

Regardless of the task distributions modules location, it generates DSTallocation information 242 from the selected task ID 240 and theselected data ID 238. The DST allocation information 242 includes datapartitioning information, task execution information, and/orintermediate result information. The task distribution module 232 sendsthe DST allocation information 242 to the DSTN module 22. Note that oneor more examples of the DST allocation information will be discussedwith reference to one or more of FIGS. 29-39.

The DSTN module 22 interprets the DST allocation information 242 toidentify the stored DS encoded data (e.g., DS error encoded data 2) andto identify the stored DS error encoded task code (e.g., DS errorencoded task code 1). In addition, the DSTN module 22 interprets the DSTallocation information 242 to determine how the data is to bepartitioned and how the task is to be partitioned. The DSTN module 22also determines whether the selected DS error encoded data 238 needs tobe converted from pillar grouping to slice grouping. If so, the DSTNmodule 22 converts the selected DS error encoded data into slicegroupings and stores the slice grouping DS error encoded data byoverwriting the pillar grouping DS error encoded data or by storing itin a different location in the memory of the DSTN module 22 (i.e., doesnot overwrite the pillar grouping DS encoded data).

The DSTN module 22 partitions the data and the task as indicated in theDST allocation information 242 and sends the portions to selected DSTexecution units of the DSTN module 22. Each of the selected DSTexecution units performs its partial task(s) on its slice groupings toproduce partial results. The DSTN module 22 collects the partial resultsfrom the selected DST execution units and provides them, as resultinformation 244, to the task distribution module. The result information244 may be the collected partial results, one or more final results asproduced by the DSTN module 22 from processing the partial results inaccordance with the DST allocation information 242, or one or moreintermediate results as produced by the DSTN module 22 from processingthe partial results in accordance with the DST allocation information242.

The task distribution module 232 receives the result information 244 andprovides one or more final results 104 therefrom to the first DST clientmodule. The final result(s) 104 may be result information 244 or aresult(s) of the task distribution module's processing of the resultinformation 244.

In concurrence with processing the selected task of the first DST clientmodule, the distributed computing system may process the selectedtask(s) of the second DST client module on the selected data(s) of thesecond DST client module. Alternatively, the distributed computingsystem may process the second DST client module's request subsequent to,or preceding, that of the first DST client module. Regardless of theordering and/or parallel processing of the DST client module requests,the second DST client module provides its selected data 238 and selectedtask 240 to a task distribution module 232. If the task distributionmodule 232 is a separate device of the distributed computing system orwithin the DSTN module, the task distribution modules 232 coupled to thefirst and second DST client modules may be the same module. The taskdistribution module 232 processes the request of the second DST clientmodule in a similar manner as it processed the request of the first DSTclient module.

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module 232 facilitating the example of FIG. 28. The taskdistribution module 232 includes a plurality of tables it uses togenerate distributed storage and task (DST) allocation information 242for selected data and selected tasks received from a DST client module.The tables include data storage information 248, task storageinformation 250, distributed task (DT) execution module information 252,and task

sub-task mapping information 246.

The data storage information table 248 includes a data identification(ID) field 260, a data size field 262, an addressing information field264, distributed storage (DS) information 266, and may further includeother information regarding the data, how it is stored, and/or how itcan be processed. For example, DS encoded data #1 has a data ID of 1, adata size of AA (e.g., a byte size of a few Terabytes or more),addressing information of Addr_(—)1_AA, and DS parameters of 3/5;SEG_(—)1; and SLC_(—)1. In this example, the addressing information maybe a virtual address corresponding to the virtual address of the firststorage word (e.g., one or more bytes) of the data and information onhow to calculate the other addresses, may be a range of virtualaddresses for the storage words of the data, physical addresses of thefirst storage word or the storage words of the data, may be a list ofslice names of the encoded data slices of the data, etc. The DSparameters may include identity of an error encoding scheme, decodethreshold/pillar width (e.g., 3/5 for the first data entry), segmentsecurity information (e.g., SEG_(—)1), per slice security information(e.g., SLC_(—)1), and/or any other information regarding how the datawas encoded into data slices.

The task storage information table 250 includes a task identification(ID) field 268, a task size field 270, an addressing information field272, distributed storage (DS) information 274, and may further includeother information regarding the task, how it is stored, and/or how itcan be used to process data. For example, DS encoded task #2 has a taskID of 2, a task size of XY, addressing information of Addr_(—)2_XY, andDS parameters of 3/5; SEG_(—)2; and SLC_(—)2. In this example, theaddressing information may be a virtual address corresponding to thevirtual address of the first storage word (e.g., one or more bytes) ofthe task and information on how to calculate the other addresses, may bea range of virtual addresses for the storage words of the task, physicaladdresses of the first storage word or the storage words of the task,may be a list of slices names of the encoded slices of the task code,etc. The DS parameters may include identity of an error encoding scheme,decode threshold/pillar width (e.g., 3/5 for the first data entry),segment security information (e.g., SEG_(—)2), per slice securityinformation (e.g., SLC_(—)2), and/or any other information regarding howthe task was encoded into encoded task slices. Note that the segmentand/or the per-slice security information include a type of encryption(if enabled), a type of compression (if enabled), watermarkinginformation (if enabled), and/or an integrity check scheme (if enabled).

The task

sub-task mapping information table 246 includes a task field 256 and asub-task field 258. The task field 256 identifies a task stored in thememory of a distributed storage and task network (DSTN) module and thecorresponding sub-task fields 258 indicates whether the task includessub-tasks and, if so, how many and if any of the sub-tasks are ordered.In this example, the task

sub-task mapping information table 246 includes an entry for each taskstored in memory of the DSTN module (e.g., task 1 through task k). Inparticular, this example indicates that task 1 includes 7 sub-tasks;task 2 does not include sub-tasks, and task k includes r number ofsub-tasks (where r is an integer greater than or equal to two).

The DT execution module table 252 includes a DST execution unit ID field276, a DT execution module ID field 278, and a DT execution modulecapabilities field 280. The DST execution unit ID field 276 includes theidentity of DST units in the DSTN module. The DT execution module IDfield 278 includes the identity of each DT execution unit in each DSTunit. For example, DST unit 1 includes three DT executions modules(e.g., 1_(—)1, 1_(—)2, and 1_(—)3). The DT execution capabilities field280 includes identity of the capabilities of the corresponding DTexecution unit. For example, DT execution module 1_(—)1 includescapabilities X, where X includes one or more of MIPS capabilities,processing resources (e.g., quantity and capability of microprocessors,CPUs, digital signal processors, co-processor, microcontrollers,arithmetic logic circuitry, and/or any other analog and/or digitalprocessing circuitry), availability of the processing resources, memoryinformation (e.g., type, size, availability, etc.), and/or anyinformation germane to executing one or more tasks.

From these tables, the task distribution module 232 generates the DSTallocation information 242 to indicate where the data is stored, how topartition the data, where the task is stored, how to partition the task,which DT execution units should perform which partial task on which datapartitions, where and how intermediate results are to be stored, etc. Ifmultiple tasks are being performed on the same data or different data,the task distribution module factors such information into itsgeneration of the DST allocation information.

FIG. 30 is a diagram of a specific example of a distributed computingsystem performing tasks on stored data as a task flow 318. In thisexample, selected data 92 is data 2 and selected tasks are tasks 1, 2,and 3. Task 1 corresponds to analyzing translation of data from onelanguage to another (e.g., human language or computer language); task 2corresponds to finding specific words and/or phrases in the data; andtask 3 corresponds to finding specific translated words and/or phrasesin translated data.

In this example, task 1 includes 7 sub-tasks: task 1_(—)1—identifynon-words (non-ordered); task 1_(—)2—identify unique words(non-ordered); task 1_(—)3—translate (non-ordered); task1_(—)4—translate back (ordered after task 1_(—)3); task 1_(—)5—compareto ID errors (ordered after task 1-4); task 1_(—)6—determine non-wordtranslation errors (ordered after task 1_(—)5 and 1_(—)1); and task1_(—)7—determine correct translations (ordered after 1_(—)5 and 1_(—)2).The sub-task further indicates whether they are an ordered task (i.e.,are dependent on the outcome of another task) or non-order (i.e., areindependent of the outcome of another task). Task 2 does not includesub-tasks and task 3 includes two sub-tasks: task 3_(—)1 translate; andtask 3_(—)2 find specific word or phrase in translated data.

In general, the three tasks collectively are selected to analyze datafor translation accuracies, translation errors, translation anomalies,occurrence of specific words or phrases in the data, and occurrence ofspecific words or phrases on the translated data. Graphically, the data92 is translated 306 into translated data 282; is analyzed for specificwords and/or phrases 300 to produce a list of specific words and/orphrases 286; is analyzed for non-words 302 (e.g., not in a referencedictionary) to produce a list of non-words 290; and is analyzed forunique words 316 included in the data 92 (i.e., how many different wordsare included in the data) to produce a list of unique words 298. Each ofthese tasks is independent of each other and can therefore be processedin parallel if desired.

The translated data 282 is analyzed (e.g., sub-task 3_(—)2) for specifictranslated words and/or phrases 304 to produce a list of specifictranslated words and/or phrases. The translated data 282 is translatedback 308 (e.g., sub-task 1_(—)4) into the language of the original datato produce re-translated data 284. These two tasks are dependent on thetranslate task (e.g., task 1_(—)3) and thus must be ordered after thetranslation task, which may be in a pipelined ordering or a serialordering. The re-translated data 284 is then compared 310 with theoriginal data 92 to find words and/or phrases that did not translate(one way and/or the other) properly to produce a list of incorrectlytranslated words 294. As such, the comparing task (e.g., sub-task1_(—)5) 310 is ordered after the translation 306 and re-translationtasks 308 (e.g., sub-tasks 1_(—)3 and 1_(—)4).

The list of words incorrectly translated 294 is compared 312 to the listof non-words 290 to identify words that were not properly translatedbecause the words are non-words to produce a list of errors due tonon-words 292. In addition, the list of words incorrectly translated 294is compared 314 to the list of unique words 298 to identify unique wordsthat were properly translated to produce a list of correctly translatedwords 296. The comparison may also identify unique words that were notproperly translated to produce a list of unique words that were notproperly translated. Note that each list of words (e.g., specific wordsand/or phrases, non-words, unique words, translated words and/orphrases, etc.,) may include the word and/or phrase, how many times it isused, where in the data it is used, and/or any other informationrequested regarding a word and/or phrase.

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30. As shown, DS encoded data 2 is storedas encoded data slices across the memory (e.g., stored in memories 88)of DST execution units 1-5; the DS encoded task code 1 (of task 1) andDS encoded task 3 are stored as encoded task slices across the memory ofDST execution units 1-5; and DS encoded task code 2 (of task 2) isstored as encoded task slices across the memory of DST execution units3-7. As indicated in the data storage information table and the taskstorage information table of FIG. 29, the respective data/task has DSparameters of 3/5 for their decode threshold/pillar width; hencespanning the memory of five DST execution units.

FIG. 32 is a diagram of an example of distributed storage and task (DST)allocation information 242 for the example of FIG. 30. The DSTallocation information 242 includes data partitioning information 320,task execution information 322, and intermediate result information 324.The data partitioning information 320 includes the data identifier (ID),the number of partitions to split the data into, address information foreach data partition, and whether the DS encoded data has to betransformed from pillar grouping to slice grouping. The task executioninformation 322 includes tabular information having a taskidentification field 326, a task ordering field 328, a data partitionfield ID 330, and a set of DT execution modules 332 to use for thedistributed task processing per data partition. The intermediate resultinformation 324 includes tabular information having a name ID field 334,an ID of the DST execution unit assigned to process the correspondingintermediate result 336, a scratch pad storage field 338, and anintermediate result storage field 340.

Continuing with the example of FIG. 30, where tasks 1-3 are to bedistributedly performed on data 2, the data partitioning informationincludes the ID of data 2. In addition, the task distribution moduledetermines whether the DS encoded data 2 is in the proper format fordistributed computing (e.g., was stored as slice groupings). If not, thetask distribution module indicates that the DS encoded data 2 formatneeds to be changed from the pillar grouping format to the slicegrouping format, which will be done the by DSTN module. In addition, thetask distribution module determines the number of partitions to dividethe data into (e.g., 2_(—)1 through 2_z) and addressing information foreach partition.

The task distribution module generates an entry in the task executioninformation section for each sub-task to be performed. For example, task1_(—)1 (e.g., identify non-words on the data) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_(—)1 through 2_z by DT execution modules1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1. For instance, DT executionmodules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 search for non-wordsin data partitions 2_(—)1 through 2_z to produce task 1_(—)1intermediate results (R1-1, which is a list of non-words). Task 1_(—)2(e.g., identify unique words) has similar task execution information astask 1_(—)1 to produce task 1_(—)2 intermediate results (R1-2, which isthe list of unique words). Task 1_(—)3 (e.g., translate) includes taskexecution information as being non-ordered (i.e., is independent),having DT execution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1translate data partitions 2_(—)1 through 2_(—)4 and having DT executionmodules 1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 translate datapartitions 2_(—)5 through 2_z to produce task 1_(—)3 intermediateresults (R1-3, which is the translated data). In this example, the datapartitions are grouped, where different sets of DT execution modulesperform a distributed sub-task (or task) on each data partition group,which allows for further parallel processing.

Task 1_(—)4 (e.g., translate back) is ordered after task 1_(—)3 and isto be executed on task 1_(—)3's intermediate result (e.g., R1-3_(—)1)(e.g., the translated data). DT execution modules 1_(—)1, 2_(—)1,3_(—)1, 4_(—)1, and 5_(—)1 are allocated to translate back task 1_(—)3intermediate result partitions R1-3_(—)1 through R1-3_(—)4 and DTexecution modules 1_(—)2, 2_(—)2, 6_(—)1, 7_(—)1, and 7_(—)2 areallocated to translate back task 1_(—)3 intermediate result partitionsR1-3_(—)5 through R1-3_z to produce task 1-4 intermediate results (R1-4,which is the translated back data).

Task 1_(—)5 (e.g., compare data and translated data to identifytranslation errors) is ordered after task 1_(—)4 and is to be executedon task 1_(—)4's intermediate results (R4-1) and on the data. DTexecution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 areallocated to compare the data partitions (2_(—)1 through 2_z) withpartitions of task 1-4 intermediate results partitions R1-4_(—)1 throughR1-4_z to produce task 1_(—)5 intermediate results (R1-5, which is thelist words translated incorrectly).

Task 1_(—)6 (e.g., determine non-word translation errors) is orderedafter tasks 1_(—)1 and 1_(—)5 and is to be executed on tasks 1_(—)1'sand 1_(—)5's intermediate results (R1-1 and R1-5). DT execution modules1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 are allocated to compare thepartitions of task 1_(—)1 intermediate results (R1-1_(—)1 throughR1-1_z) with partitions of task 1-5 intermediate results partitions(R1-5_(—)1 through R1-5_z) to produce task 1_(—)6 intermediate results(R1-6, which is the list translation errors due to non-words).

Task 1_(—)7 (e.g., determine words correctly translated) is orderedafter tasks 1_(—)2 and 1_(—)5 and is to be executed on tasks 1_(—)2'sand 1_(—)5's intermediate results (R1-1 and R1-5). DT execution modules1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 are allocated to compare thepartitions of task 1_(—)2 intermediate results (R1-2_(—)1 throughR1-2_z) with partitions of task 1-5 intermediate results partitions(R1-5_(—)1 through R1-5_z) to produce task 1_(—)7 intermediate results(R1-7, which is the list of correctly translated words).

Task 2 (e.g., find specific words and/or phrases) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_(—)1 through 2_z by DT execution modules3_(—)1, 4_(—)1, 5_(—)1, 6_(—)1, and 7_(—)1. For instance, DT executionmodules 3_(—)1, 4_(—)1, 5_(—)1, 6_(—)1, and 7_(—)1 search for specificwords and/or phrases in data partitions 2_(—)1 through 2_z to producetask 2 intermediate results (R2, which is a list of specific wordsand/or phrases).

Task 3_(—)2 (e.g., find specific translated words and/or phrases) isordered after task 1_(—)3 (e.g., translate) is to be performed onpartitions R1-3_(—)1 through R1-3_z by DT execution modules 1_(—)2,2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2. For instance, DT execution modules1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 search for specifictranslated words and/or phrases in the partitions of the translated data(R1-3_(—)1 through R1-3_z) to produce task 3_(—)2 intermediate results(R3-2, which is a list of specific translated words and/or phrases).

For each task, the intermediate result information indicates which DSTunit is responsible for overseeing execution of the task and, if needed,processing the partial results generated by the set of allocated DTexecution units. In addition, the intermediate result informationindicates a scratch pad memory for the task and where the correspondingintermediate results are to be stored. For example, for intermediateresult R1-1 (the intermediate result of task 1_(—)1), DST unit 1 isresponsible for overseeing execution of the task 1_(—)1 and coordinatesstorage of the intermediate result as encoded intermediate result slicesstored in memory of DST execution units 1-5. In general, the scratch padis for storing non-DS encoded intermediate results and the intermediateresult storage is for storing DS encoded intermediate results.

FIGS. 33-38 are schematic block diagrams of the distributed storage andtask network (DSTN) module performing the example of FIG. 30. In FIG.33, the DSTN module accesses the data 92 and partitions it into aplurality of partitions 1-z in accordance with distributed storage andtask network (DST) allocation information. For each data partition, theDSTN identifies a set of its DT (distributed task) execution modules 90to perform the task (e.g., identify non-words (i.e., not in a referencedictionary) within the data partition) in accordance with the DSTallocation information. From data partition to data partition, the setof DT execution modules 90 may be the same, different, or a combinationthereof (e.g., some data partitions use the same set while other datapartitions use different sets).

For the first data partition, the first set of DT execution modules(e.g., 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 per the DST allocationinformation of FIG. 32) executes task 1_(—)1 to produce a first partialresult 102 of non-words found in the first data partition. The secondset of DT execution modules (e.g., 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and5_(—)1 per the DST allocation information of FIG. 32) executes task1_(—)1 to produce a second partial result 102 of non-words found in thesecond data partition. The sets of DT execution modules (as per the DSTallocation information) perform task 1_(—)1 on the data partitions untilthe “z” set of DT execution modules performs task 1_(—)1 on the “zth”data partition to produce a “zth” partial result 102 of non-words foundin the “zth” data partition.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results toproduce the first intermediate result (R1-1), which is a list ofnon-words found in the data. For instance, each set of DT executionmodules 90 stores its respective partial result in the scratchpad memoryof DST execution unit 1 (which is identified in the DST allocation ormay be determined by DST execution unit 1). A processing module of DSTexecution 1 is engaged to aggregate the first through “zth” partialresults to produce the first intermediate result (e.g., R1_(—)1). Theprocessing module stores the first intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the first intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of non-words is of a sufficient size to partition(e.g., greater than a Terabytes). If yes, it partitions the firstintermediate result (R1-1) into a plurality of partitions (e.g.,R1-1_(—)1 through R1-1_m). If the first intermediate result is not ofsufficient size to partition, it is not partitioned.

For each partition of the first intermediate result, or for the firstintermediate result, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 34, the DSTN module is performing task 1_(—)2 (e.g., find uniquewords) on the data 92. To begin, the DSTN module accesses the data 92and partitions it into a plurality of partitions 1-z in accordance withthe DST allocation information or it may use the data partitions of task1_(—)1 if the partitioning is the same. For each data partition, theDSTN identifies a set of its DT execution modules to perform task 1_(—)2in accordance with the DST allocation information. From data partitionto data partition, the set of DT execution modules may be the same,different, or a combination thereof. For the data partitions, theallocated set of DT execution modules executes task 1_(—)2 to produce apartial results (e.g., 1^(st) through “zth”) of unique words found inthe data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results102 of task 1_(—)2 to produce the second intermediate result (R1-2),which is a list of unique words found in the data 92. The processingmodule of DST execution 1 is engaged to aggregate the first through“zth” partial results of unique words to produce the second intermediateresult. The processing module stores the second intermediate result asnon-DS error encoded data in the scratchpad memory or in another sectionof memory of DST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the second intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of unique words is of a sufficient size to partition(e.g., greater than a Terabytes). If yes, it partitions the secondintermediate result (R1-2) into a plurality of partitions (e.g.,R1-2_(—)1 through R1-2_m). If the second intermediate result is not ofsufficient size to partition, it is not partitioned.

For each partition of the second intermediate result, or for the secondintermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 35, the DSTN module is performing task 1_(—)3 (e.g., translate)on the data 92. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions 1-z in accordance with theDST allocation information or it may use the data partitions of task1_(—)1 if the partitioning is the same. For each data partition, theDSTN identifies a set of its DT execution modules to perform task 1_(—)3in accordance with the DST allocation information (e.g., DT executionmodules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 translate datapartitions 2_(—)1 through 2_(—)4 and DT execution modules 1_(—)2,2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 translate data partitions 2_(—)5through 2_z). For the data partitions, the allocated set of DT executionmodules 90 executes task 1_(—)3 to produce partial results 102 (e.g.,1^(st) through “zth”) of translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_(—)3 to produce the third intermediate result (R1-3), which istranslated data. The processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of translated data toproduce the third intermediate result. The processing module stores thethird intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the third intermediate result (e.g., translateddata). To begin the encoding, the DST client module partitions the thirdintermediate result (R1-3) into a plurality of partitions (e.g.,R1-3_(—)1 through R1-3_y). For each partition of the third intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes 3/5 decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 2-6 per the DST allocationinformation).

As is further shown in FIG. 35, the DSTN module is performing task1_(—)4 (e.g., retranslate) on the translated data of the thirdintermediate result. To begin, the DSTN module accesses the translateddata (from the scratchpad memory or from the intermediate result memoryand decodes it) and partitions it into a plurality of partitions inaccordance with the DST allocation information. For each partition ofthe third intermediate result, the DSTN identifies a set of its DTexecution modules 90 to perform task 1_(—)4 in accordance with the DSTallocation information (e.g., DT execution modules 1_(—)1, 2_(—)1,3_(—)1, 4_(—)1, and 5_(—)1 are allocated to translate back partitionsR1-3_(—)1 through R1-3_(—)4 and DT execution modules 1_(—)2, 2_(—)2,6_(—)1, 7_(—)1, and 7_(—)2 are allocated to translate back partitionsR1-3_(—)5 through R1-3_z). For the partitions, the allocated set of DTexecution modules executes task 1_(—)4 to produce partial results 102(e.g., 1^(st) through “zth”) of re-translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_(—)4 to produce the fourth intermediate result (R1-4), which isretranslated data. The processing module of DST execution 3 is engagedto aggregate the first through “zth” partial results of retranslateddata to produce the fourth intermediate result. The processing modulestores the fourth intermediate result as non-DS error encoded data inthe scratchpad memory or in another section of memory of DST executionunit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the fourth intermediate result (e.g., retranslateddata). To begin the encoding, the DST client module partitions thefourth intermediate result (R1-4) into a plurality of partitions (e.g.,R1-4_(—)1 through R1-4_z). For each partition of the fourth intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes 3/5 decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 3-7 per the DST allocationinformation).

In FIG. 36, a distributed storage and task network (DSTN) module isperforming task 1_(—)5 (e.g., compare) on data 92 and retranslated dataof FIG. 35. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions in accordance with the DSTallocation information or it may use the data partitions of task 1_(—)1if the partitioning is the same. The DSTN module also accesses theretranslated data from the scratchpad memory, or from the intermediateresult memory and decodes it, and partitions it into a plurality ofpartitions in accordance with the DST allocation information. The numberof partitions of the retranslated data corresponds to the number ofpartitions of the data.

For each pair of partitions (e.g., data partition 1 and retranslateddata partition 1), the DSTN identifies a set of its DT execution modules90 to perform task 1_(—)5 in accordance with the DST allocationinformation (e.g., DT execution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1,and 5_(—)1). For each pair of partitions, the allocated set of DTexecution modules executes task 1_(—)5 to produce partial results 102(e.g., 1^(st) through “zth”) of a list of incorrectly translated wordsand/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results oftask 1_(—)5 to produce the fifth intermediate result (R1-5), which isthe list of incorrectly translated words and/or phrases. In particular,the processing module of DST execution 1 is engaged to aggregate thefirst through “zth” partial results of the list of incorrectlytranslated words and/or phrases to produce the fifth intermediateresult. The processing module stores the fifth intermediate result asnon-DS error encoded data in the scratchpad memory or in another sectionof memory of DST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the fifth intermediate result. To begin theencoding, the DST client module partitions the fifth intermediate result(R1-5) into a plurality of partitions (e.g., R1-5_(—)1 through R1-5_z).For each partition of the fifth intermediate result, the DST clientmodule uses the DS error encoding parameters of the data (e.g., DSparameters of data 2, which includes 3/5 decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 1-5 per the DST allocation information).

As is further shown in FIG. 36, the DSTN module is performing task1_(—)6 (e.g., translation errors due to non-words) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of non-words (e.g., the firstintermediate result R1-1). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-1_(—)1 and partitionR1-5_(—)1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_(—)6 in accordance with the DST allocation information(e.g., DT execution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1).For each pair of partitions, the allocated set of DT execution modulesexecutes task 1_(—)6 to produce partial results 102 (e.g., 1^(st)through “zth”) of a list of incorrectly translated words and/or phrasesdue to non-words.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_(—)6 to produce the sixth intermediate result (R1-6), which isthe list of incorrectly translated words and/or phrases due tonon-words. In particular, the processing module of DST execution 2 isengaged to aggregate the first through “zth” partial results of the listof incorrectly translated words and/or phrases due to non-words toproduce the sixth intermediate result. The processing module stores thesixth intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the sixth intermediate result. To begin theencoding, the DST client module partitions the sixth intermediate result(R1-6) into a plurality of partitions (e.g., R1-6_(—)1 through R1-6_z).For each partition of the sixth intermediate result, the DST clientmodule uses the DS error encoding parameters of the data (e.g., DSparameters of data 2, which includes 3/5 decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 2-6 per the DST allocation information).

As is still further shown in FIG. 36, the DSTN module is performing task1_(—)7 (e.g., correctly translated words and/or phrases) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of unique words (e.g., the secondintermediate result R1-2). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-2_(—)1 and partitionR1-5_(—)1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_(—)7 in accordance with the DST allocation information(e.g., DT execution modules 1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2).For each pair of partitions, the allocated set of DT execution modulesexecutes task 1_(—)7 to produce partial results 102 (e.g., 1^(st)through “zth”) of a list of correctly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_(—)7 to produce the seventh intermediate result (R1-7), which isthe list of correctly translated words and/or phrases. In particular,the processing module of DST execution 3 is engaged to aggregate thefirst through “zth” partial results of the list of correctly translatedwords and/or phrases to produce the seventh intermediate result. Theprocessing module stores the seventh intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the seventh intermediate result. To begin theencoding, the DST client module partitions the seventh intermediateresult (R1-7) into a plurality of partitions (e.g., R1-7_(—)1 throughR1-7_z). For each partition of the seventh intermediate result, the DSTclient module uses the DS error encoding parameters of the data (e.g.,DS parameters of data 2, which includes 3/5 decode threshold/pillarwidth ratio) to produce slice groupings. The slice groupings are storedin the intermediate result memory (e.g., allocated memory in thememories of DST execution units 3-7 per the DST allocation information).

In FIG. 37, the distributed storage and task network (DSTN) module isperforming task 2 (e.g., find specific words and/or phrases) on the data92. To begin, the DSTN module accesses the data and partitions it into aplurality of partitions 1-z in accordance with the DST allocationinformation or it may use the data partitions of task 1_(—)1 if thepartitioning is the same. For each data partition, the DSTN identifies aset of its DT execution modules 90 to perform task 2 in accordance withthe DST allocation information. From data partition to data partition,the set of DT execution modules may be the same, different, or acombination thereof. For the data partitions, the allocated set of DTexecution modules executes task 2 to produce partial results 102 (e.g.,1^(st) through “zth”) of specific words and/or phrases found in the datapartitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 7 is assigned to process the first through “zth” partial results oftask 2 to produce task 2 intermediate result (R2), which is a list ofspecific words and/or phrases found in the data. The processing moduleof DST execution 7 is engaged to aggregate the first through “zth”partial results of specific words and/or phrases to produce the task 2intermediate result. The processing module stores the task 2intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 7.

DST execution unit 7 engages its DST client module to slice groupingbased DS error encode the task 2 intermediate result. To begin theencoding, the DST client module determines whether the list of specificwords and/or phrases is of a sufficient size to partition (e.g., greaterthan a Terabytes). If yes, it partitions the task 2 intermediate result(R2) into a plurality of partitions (e.g., R2_(—)1 through R2_m). If thetask 2 intermediate result is not of sufficient size to partition, it isnot partitioned.

For each partition of the task 2 intermediate result, or for the task 2intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, and 7).

In FIG. 38, the distributed storage and task network (DSTN) module isperforming task 3 (e.g., find specific translated words and/or phrases)on the translated data (R1-3). To begin, the DSTN module accesses thetranslated data (from the scratchpad memory or from the intermediateresult memory and decodes it) and partitions it into a plurality ofpartitions in accordance with the DST allocation information. For eachpartition, the DSTN identifies a set of its DT execution modules toperform task 3 in accordance with the DST allocation information. Frompartition to partition, the set of DT execution modules may be the same,different, or a combination thereof. For the partitions, the allocatedset of DT execution modules 90 executes task 3 to produce partialresults 102 (e.g., 1^(st) through “zth”) of specific translated wordsand/or phrases found in the data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 5 is assigned to process the first through “zth” partial results oftask 3 to produce task 3 intermediate result (R3), which is a list ofspecific translated words and/or phrases found in the translated data.In particular, the processing module of DST execution 5 is engaged toaggregate the first through “zth” partial results of specific translatedwords and/or phrases to produce the task 3 intermediate result. Theprocessing module stores the task 3 intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 7.

DST execution unit 5 engages its DST client module to slice groupingbased DS error encode the task 3 intermediate result. To begin theencoding, the DST client module determines whether the list of specifictranslated words and/or phrases is of a sufficient size to partition(e.g., greater than a Terabytes). If yes, it partitions the task 3intermediate result (R3) into a plurality of partitions (e.g., R3_(—)1through R3_m). If the task 3 intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the task 3 intermediate result, or for the task 3intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, 5, and 7).

FIG. 39 is a diagram of an example of combining result information intofinal results 104 for the example of FIG. 30. In this example, theresult information includes the list of specific words and/or phrasesfound in the data (task 2 intermediate result), the list of specifictranslated words and/or phrases found in the data (task 3 intermediateresult), the list of non-words found in the data (task 1 firstintermediate result R1-1), the list of unique words found in the data(task 1 second intermediate result R1-2), the list of translation errorsdue to non-words (task 1 sixth intermediate result R1-6), and the listof correctly translated words and/or phrases (task 1 seventhintermediate result R1-7). The task distribution module provides theresult information to the requesting DST client module as the results104.

FIG. 40A is a schematic block diagram of another embodiment of adistributed computing system that includes the distributed storage andtask network (DSTN) managing unit 18 of FIG. 1, the distributed storageand task (DST) integrity processing unit 20 of FIG. 1, the network 24 ofFIG. 1, and a DSTN execution unit set 350. The system may provide a DSTNand/or a dispersed storage network (DSN). The DSTN execution unit set350 includes a plurality of DST execution units 36 of FIG. 1.

The system functions to classify DST execution units 36 as underutilizedresources 351 or over utilized resources 352 and to prioritize executionof pending resource demands based on the classifications. Anunderutilized resource has more resource capacity than resourceutilization and an over utilized resource has less resource capacitythan resource demand. The DST integrity processing unit 20 performs aseries of steps to classify the DST execution units 36.

In an example of operation, the DST integrity processing unit 20 obtainscost information 354 for the DSTN execution unit set 350. The costinformation 354 includes one or more of bandwidth costs of communicationlinks, burst bandwidth cost when capacity is exceeded, fixed capacitycost, variable power costs of the facility at different times a day,cost of time for servicing field components, average time it takes toservice a failed component, and varying costs by time of day or day ofweek. The obtaining includes one or more of initiating a query to the DSmanaging unit 18, initiating a query to an external entity, receivingthe cost information 354, performing a lookup, accessing a billingrecord, and calculating based on multiple historical cost records.

The DST integrity processing unit 20 obtains resource utilizationinformation 356 of the plurality of DST execution units 36. The resourceutilization information 356 includes one or more of a fixed bandwidthcapacity utilization level, a burst bandwidth utilization level,bandwidth utilization by time of day and day of week, write availabilityinformation, read reliability information, utilization by DSN addressrange and computing processing level utilization. The obtaining includesat least one of initiating a resource utilization request to at leastsome of the plurality of DST execution units 36 and receiving theresource utilization information 356 from one or more DST executionunits 36 of the plurality of DST execution units 36.

Having received the resource utilization information 356, the DSTintegrity processing unit 20 identifies pending resource demand fortasks associated with the plurality of DST execution units 36. Thepending resource demand includes tasks related to one or more ofrebuilding slices to be rebuilt, performing distributed computingpartial tasks, maintenance tasks, update tasks, and performing dataaccess tasks (e.g., write, read, delete, list). The identifying includesone or more of initiating a query to the at least some of the DSTexecution units 36, receiving a task list, accessing a task list,receiving one or more task requests, interpreting a maintenanceschedule, and identifying an encoded data slice for rebuilding.

The DST integrity processing unit 20 groups the DST execution units 36into the underutilized and over utilized resource groups based on one ormore of the resource utilization information 356 and the costinformation 354. The grouping includes, for each DST execution unit 36,identifying the DST execution unit 36 as underutilized when a resourceutilization level of the DST execution unit 36 is less than autilization threshold level based on the cost information. The groupingfurther includes identifying the DST execution unit 36 as over utilizedwhen a resource execution level of the DST execution unit 36 is lessthan a pending resource demand level for the DST execution unit 36 basedon the cost information.

The DST integrity processing unit 20 performs a series of further tasksto prioritize the execution of the pending resource demands based on theclassifications. The DST integrity processing unit 20 issueshigh-priority rebuilding information 358 to DST execution units 36 ofthe underutilized resources 351 to include tasks based on the pendingresource demand. The issuing includes generating the high-priorityrebuilding information 358 to include pending rebuilding tasks. The DSTintegrity processing unit 20 determines whether sufficient capacity isavailable within the underutilized resources 351 to service the pendingresource demand in accordance with a goal performance level. Forexample, the DST integrity processing unit 20 indicates that capacity isnot available when an estimated performance level of the underutilizedresources is less than the goal performance level. For instance, anestimated time to completion for the DST execution units 36 to perform anext ten rebuilding tasks is greater than a time to completion goal.When sufficient capacity is not available, the DST integrity processingunit 20 issues low priority rebuilding information 360 to the DSTexecution units 36 of the over utilized resources 352 to includeremaining tasks based on the pending resource demand. The issuingincludes generating the low priority rebuilding information 360 toinclude the remaining tasks of the pending resource demand. Forinstance, the DST integrity processing unit 20 assigns two of the nextten rebuilding tasks rebuilding tasks to the DST execution units 36 ofthe over utilized resources 352.

FIG. 40B is a flowchart illustrating an example of prioritizingrebuilding data. The method begins with step 362 where a processingmodule (e.g., of a distributed storage and task (DST) integrityprocessing unit 20) obtains cost information for a distributed storageand task network (DSTN). The method continues at step 364 where theprocessing module obtains resource utilization information for DSTexecution units of the DSTN. The method continues at step 366 where theprocessing module identifies pending resource demands with regards tothe DST execution units. The method continues at step 368 where theprocessing module groups (e.g., classifies) the DST execution units intounderutilized and over utilized resource groups.

The method continues at step 370 where the processing module issueshigh-priority rebuilding information (e.g., including at least somepending rebuilding tasks of pending rebuilding tasks) to the DSTexecution units of the underutilized resources. The method continues atstep 372 where the processing module determines whether sufficientcapacity is available within the underutilized resources to performtasks of the pending resource demand. When sufficient capacity is notavailable within the underutilized resources, the method continues atstep 374 where the processing module issues low priority rebuildinginformation to the DST execution units of the over utilized resources toperform remaining tasks (e.g., at least some of the rebuilding tasks) ofthe pending resource demand.

FIG. 41A is a schematic block diagram of another embodiment of adistributed computing system that includes the distributed storage andtask network (DSTN) managing unit 18 of FIG. 1, the distributed storageand task (DST) processing unit 16 of FIG. 1, the network 24 of FIG. 1,and the DSTN execution unit set 350 of FIG. 40A. The DSTN execution unitset 350 includes a plurality of DST execution units 36 of FIG. 1.

The system functions to classify DST execution units 36 as underutilizedresources 351 or overutilized resources 352 and to prioritize executionof pending resource demands based on the classifications. The DSTprocessing unit 16 performs a series of steps to classify the DSTexecution units 36. In an example of operation, the DST processing unit16 obtains cost information 354 for the DSTN execution unit set 350.

The DST processing unit 16 obtains resource utilization information 356of the plurality of DST execution units 36. The obtaining includes atleast one of initiating a resource utilization request to at least someof the plurality of DST execution units 36 and receiving the resourceutilization information 356 from one or more DST execution units 36 ofthe plurality of DST execution units 36. The DST integrity processingunit 20 identifies pending resource demand for tasks associated with theplurality of DST execution units 36. The pending resource demandincludes tasks related to one or more of rebuilding slices to berebuilt, performing distributed computing partial tasks, maintenancetasks, update tasks, and performing data access tasks (e.g., write,read, delete, list). The identifying includes one or more of initiatinga query to the at least some of the DST execution units 36, receiving atask list, accessing a task list, receiving one or more task requests,interpreting a maintenance schedule, and identifying an encoded dataslice for rebuilding.

The DST processing unit 16 groups the DST execution units 36 into theunderutilized and over utilized resource groups based on one or more ofthe resource utilization information 356 and the cost information 354.The grouping includes, for each DST execution unit 36, identifying theDST execution unit 36 as underutilized when a resource utilization levelof the DST execution unit 36 is less than a utilization threshold levelbased on the cost information 354. The grouping further includesidentifying the DST execution unit 36 as over utilized when a resourceexecution level of the DST execution unit 36 is less than a pendingresource demand level for the DST execution unit 36 based on the costinformation 354.

The DST processing unit 16 performs a series of further tasks toprioritize the execution of the pending resource demands based on theclassifications. The DST processing unit 16 issues high-priority readaccess information 376 to DST execution units 36 of the underutilizedresources 351 to include tasks based on the pending resource demand. Theissuing includes generating the high-priority read access information376 to include at least some read slice requests of a read thresholdnumber of read slice requests of the pending resource demand. Thegenerating includes determining a number of the at least some read slicerequests based on one or more of the resource utilization information inthe cost information. For example, the DST processing unit 16 generates11 read slice requests when the underutilized resources includes 11 DSTexecution units 36. The DST processing unit 16 determines whether thehigh-priority read access information includes the read threshold numberof read slice requests. For example, the DST processing unit 16indicates that the high-priority read access information 376 does notinclude the read threshold number of read slice requests when the readthreshold is 12 and the DST processing unit 16 generated the 11 readslice requests.

When the at least the read threshold number of read slice requests arenot included, the DST processing unit 16 issues low priority read accessinformation 378 to the DST execution units 36 of the over utilizedresources 352 to include remaining read slice requests of the readthreshold number of read slice requests. The issuing includesidentifying DST execution units 36 of the over utilized DST executionunits 36 that are least over utilized based on corresponding resourceutilization information 356, selecting the remaining read slice requeststhat are associated with the identified DST execution units 36,generating the remaining read slice requests, and outputting theremaining read slice requests to the identified DST execution units 36.

FIG. 41B is a flowchart illustrating an example of prioritizing readingdata, which include similar steps to FIG. 40B. The method begins withsteps 362-368 of FIG. 40B where a processing module (e.g., of adistributed storage and task (DST) integrity processing unit 20) obtainscost information for a distributed storage and task network (DSTN),obtains resource utilization information for DST execution units of theDSTN, identifies pending resource demand with regards to the DSTexecution units, and groups the DST execution units into underutilizedand over utilized resource groups.

The method continues at step 380 where the processing module issueshigh-priority read access information to the DST execution units of theunderutilized resources to include at least some read slice requests ofa read threshold number of read slice requests of the pending resourcedemand. The method continues at step 382 where the processing moduledetermines whether the high-priority read access information includesthe read threshold number of read slice requests. When the high-priorityread access information does not include the read threshold number ofread slice requests, the method continues at step 384 where theprocessing module issues low priority read access information to the DSTexecution units of the over utilized resources. The low priority readaccess information includes remaining read slice requests of the readthreshold number of read slice requests. The issuing includes selectingcorresponding DST execution units of the DST execution units of the overutilized resources that are least over utilized.

FIG. 42A is a schematic block diagram of another embodiment of adistributed computing system that includes the distributed storage andtask network (DSTN) managing unit 18 of FIG. 1, the distributed storageand task (DST) processing unit 16 of FIG. 1, the network 24 of FIG. 1,and two or more DSTN execution unit sets 350. Each DSTN execution unitset 350 of the two or more DSTN execution unit sets includes a set ofDST execution units 36 of FIG. 1.

The system functions to, for each DSTN execution unit set 350, classifyassociated DST execution units 36 as underutilized resources 351 oroverutilized resources 352 and to prioritize execution of pendingresource demands based on the classifications. The DST processing unit16 performs a series of steps to classify the DST execution units 36. Inan example of operation, the DST processing unit 16 obtains costinformation 354 for the DSTN execution unit sets 350. The obtainingincludes one or more of initiating a query to the DS managing unit 18,initiating a query to an external entity, receiving the cost information354, performing a lookup, accessing a billing record, and determiningbased on multiple historical cost records.

For each DSTN execution unit set 350, the DST processing unit 16 obtainsresource utilization information 356 of the set of DST execution units.The obtaining includes at least one of initiating a resource utilizationrequest to at least some of the set of DST execution units 36 andreceiving the resource utilization information 356 from one or more DSTexecution units 36 of the set of DST execution units 36.

Having received the resource utilization information 356, DST processingunit 16 identifies pending resource demand for tasks associated witheach set of DST execution units. The pending resource demand includestasks related to one or more of rebuilding slices to be rebuilt,performing distributed computing partial tasks, maintenance tasks,update tasks, and performing data access tasks (e.g., write, read,delete, list). The identifying includes one or more of initiating aquery to the at least some of the DST execution units 36, receiving atask list, accessing a task list, receiving one or more task requests,interpreting a maintenance schedule, and identifying an encoded dataslice for rebuilding.

For each DSTN execution unit set, the DST processing unit 16 groups theDST execution units 36 into the underutilized and the over utilizedresource groups based on one or more of the resource utilizationinformation 356 and the cost information 354. The grouping includes, foreach DST execution unit 36, identifying the DST execution unit 36 asunderutilized when a resource utilization level of the DST executionunit 36 is less than a utilization threshold level based on the costinformation 354. The grouping further includes identifying the DSTexecution unit 36 as over utilized when a resource execution level ofthe DST execution unit 36 is less than a pending resource demand levelfor the DST execution unit 36 based on the cost information 354.

The DST processing unit 16 performs a series of further tasks toprioritize the execution of the pending resource demands based on theclassifications. The DST processing unit 16 selects one DST executionunit set of the at least two DSTN execution unit sets based on one ormore of the resource utilization information 356 and the pendingresource demand. For example, the DST processing unit 16 selects the oneDST execution unit set associated with a highest number of DST executionunits 36 of a corresponding underutilized resources 351.

The DST processing unit 16 issues high-priority write access information386 to DST execution units 36 of the underutilized resources 351 toinclude tasks based on the pending resource demand. The issuing includesgenerating the high-priority write access information 386 to include atleast some write slice requests of a write threshold number of writeslice requests of the pending resource demand. The generating includesdetermining a number of the at least some write slice requests based onone or more of the resource utilization information in the costinformation. For example, the DST processing unit 16 generates 13 writeslice requests when the underutilized resources 351 includes 13 DSTexecution units 36 of the one DSTN execution unit set. The DSTprocessing unit 16 determines whether the high-priority read accessinformation 386 includes the write threshold number of write slicerequests. For example, the DST processing unit 16 indicates that thehigh-priority write access information 386 does not include the writethreshold number of write slice requests when the write threshold is 14and the DST processing unit 16 generated the 13 write slice requests.

When the at least the write threshold number of write slice requests arenot included, the DST processing unit 16 issues low priority writeaccess information 388 to the DST execution units 36 of the overutilizedresources 352 of the one DSTN execution unit set to include remainingwrite slice requests of the write threshold number of write slicerequests. The issuing includes identifying DST execution units 36 of theover utilized DST execution units 36 that are least over utilized basedon corresponding resource utilization information 356, selecting theremaining write slice requests that are associated with the identifiedDST execution units 36, generating the remaining write slice requests,and outputting the remaining write slice requests to the identified DSTexecution units 36.

FIG. 42B is a flowchart illustrating an example of prioritizing storingdata, which include similar steps to FIG. 40B. The method begins withstep 362 of FIG. 40B where a processing module (e.g., of a distributedstorage and task (DST) processing unit) obtains cost information for adistributed storage and task network (DSTN). For each storage unit setof a plurality of storage unit sets of the DSTN, the method continues atstep 390 where the processing module obtains resource utilizationinformation for DST execution units associated with the storage unit set(e.g., initiate a query, perform a test, perform a lookup, receiving anerror message, access historical records, receive the resourceutilization information). For each storage unit set, the methodcontinues at step 392 where the processing module identifies pendingresource demand with regards to the DST execution units associated withthe storage unit set (e.g., query one or more DST execution units,access a task list, receive one or more requests, identify encoded dataslices for writing). For each storage unit set, the method continues atstep 394 where the processing module groups the DST execution units intounderutilized and over utilized resource groups.

The method continues at step 396 where the processing module selects astorage unit set of the plurality of storage unit sets for storing thedata. The selecting may be based on one or more of the resourceutilization information and the pending resource demand. For theexample, the processing module selects the storage unit set associatedwith a highest number of DST execution units of the underutilizedresources. The method continues at step 398 where the processing moduleissues high-priority write access information to the DST execution unitsof the underutilized resources of the selected storage unit set. Theissue includes outputting at least some write slice requests of a writethreshold number of write slice requests of the pending resource demand.The method continues at step 400 where the processing module determineswhether the high-priority write access information includes at least thewrite threshold number of write slice requests. When the high-prioritywrite access information does not include the at least the writethreshold number of write slice requests, the method continues at step402 where the processing module issues low priority write accessinformation to the DST execution units of the over utilized resources ofthe selected storage unit set. The issue includes including remainingwrite slice requests of the write threshold number of write slicerequests.

FIG. 43A is a schematic block diagram of another embodiment of adistributed computing system that includes the distributed storage andtask network (DSTN) managing unit 18 of FIG. 1, the distributed storageand task (DST) processing unit 16 of FIG. 1, the network 24 of FIG. 1,and two or more DSTN execution unit sets 350. Each DSTN execution unitset of the two or more DSTN execution unit sets includes a set of DSTexecution units 36 of FIG. 1.

The system functions to, for each DSTN execution unit set 350, classifyDST execution units 36 as underutilized resources 351 or overutilizedresources 352 and to prioritize execution of pending resource demandsbased on the classifications. The DST processing unit 16 performs aseries of steps to classify the DST execution units 36. In an example ofoperation, the DST processing unit 16 obtains cost information 354 forthe DSTN execution unit sets. The obtaining includes at least one ofinitiating a query to the DS managing unit 18, initiating a query to anexternal entity, receiving the cost information 354, performing alookup, accessing a billing record, and determining based on multiplehistorical cost records.

For each DSTN execution unit set, the DST processing unit 16 obtainsresource utilization information 356 of the set of DST execution units350. The obtaining includes at least one of initiating a resourceutilization request to at least some of the set of DST execution units36 and receiving the resource utilization information 356 from one ormore DST execution units 36 of the set of DST execution units 36. TheDST processing unit 16 identifies pending resource demand for tasksassociated with each set of DST execution units. The pending resourcedemand includes tasks related to one or more of rebuilding slices to berebuilt, performing distributed computing partial tasks, maintenancetasks, update tasks, and performing data access tasks (e.g., write,read, delete, list). The identifying includes one or more of initiatinga query to the at least some of the DST execution units 36, receiving atask list, accessing a task list, receiving one or more task requests,interpreting a maintenance schedule, and identifying an encoded dataslice for rebuilding.

For each DSTN execution unit set 350, the DST processing unit 16 groupsthe DST execution units 36 into the underutilized and the overutilizedresource groups based on one or more of the resource utilizationinformation 356 and the cost information 354. The grouping includes, foreach DST execution unit 36, identifying the DST execution unit 36 asunderutilized when a resource utilization level of the DST executionunit 36 is less than a utilization threshold level based on the costinformation 354. The grouping further includes identifying the DSTexecution unit 36 as over utilized when a resource execution level ofthe DST execution unit 36 is less than a pending resource demand levelfor the DST execution unit 36 based on the cost information 354.

The DST processing unit 16 performs a series of further tasks toprioritize the execution of the pending resource demands based on theclassifications. The DST processing unit 16 selects one DST executionunit set of the at least two DSTN execution unit sets based on one ormore of the resource utilization information 356 and the pendingresource demand. For example, the DST processing unit 16 selects the oneDST execution unit set associated with a highest number of DST executionunits 36 of a corresponding underutilized resources, where the DSTexecution units 36 of the underutilized resources 351 are capable ofperforming partial tasks of distributed computing tasks.

The DST processing unit 16 issues high-priority task information 404 toDST execution units 36 of the underutilized resources 351 to includetasks based on the pending resource demand. The issuing includesgenerating the high-priority task information 404 to include write slicerequests with data for a distributed computing task and partial tasksperformed on the data for the distributed computing task. The generatingincludes determining a number of partial tasks and data to distributebased on one or more of the resource utilization information 356 and thecost information 354. For example, the DST processing unit 16distributes eight of ten partial tasks to the DST execution units of theunderutilized resources 351 when an estimated performance of the DSTexecution units of the underutilized resources 351 compares favorably toa desired performance level to execute the eight partial tasks. The DSTprocessing unit 16 determines whether the high-priority task information404 includes a sufficient number of tasks to meet or exceed a taskexecution performance goal. For example, the DST processing unit 16indicates that the high-priority task information 404 does not includethe sufficient number of tasks when the high-priority task information404 includes the eight of the 10 partial tasks for execution.

When the sufficient number of tasks are not included in thehigh-priority task information 404, the DST processing unit 16 issueslow priority task information 406 to the DST execution units 36 of theoverutilized resources 352 of the one DSTN execution unit set to includeremaining tasks to meet or exceed the task execution performance goal.The issuing includes generating the low priority task information toinclude the remaining tasks and sending the low priority taskinformation 406 to at least some of the DST execution units 36 of theoverutilized resources 352 of the one DST execution unit set.

FIG. 43B is a flowchart illustrating an example of prioritizingdistributed computing tasks, which include similar steps to FIGS. 40Band 42B. The method begins with step 362 of FIG. 40B where a processingmodule (e.g., of a distributed storage and task (DST) processing unit)obtains cost information for a distributed storage and task network(DSTN). The method continues with steps 390-394 of FIG. 42B where, foreach storage set of a plurality of storage sets, the processing moduleobtains resource utilization information for DST execution units of theDSTN, identifies pending resource demand with regards to the DSTexecution units, and groups the DST execution units into underutilizedand over utilized resource groups.

The method continues at step 408 where the processing module selects astorage unit set of the plurality of storage unit sets for execution ofa distributed computing task. The selecting is based on one or more ofthe resource utilization information and the pending resource demand.The method continues at step 410 where the processing module issueshigh-priority task information to the DST execution units of theunderutilized resources of the selected storage unit set. The issuingincludes generating the high-priority task information to include atleast some (e.g., enough to match capacity) partial tasks of a set ofpartial tasks of the distributed computing task.

The method continues at step 412 where the processing module determineswhether a sufficient number of DST execution units have been assigneddistributed computing tasks. The processing module indicates that asufficient number have not been assigned when all data for thedistributed computing task and all partial tasks for the distributedcomputing task have not been assigned DST execution units (e.g., notenough capacity so far). When the sufficient number of DST executionunits have not been assigned, the method continues at step 414 where theprocessing module issues low priority task information to the DSTexecution units of the over utilized resources. The issuing includesgenerating the low priority task information to include remainingpartial tasks (e.g., and associated remaining data) of the set ofpartial tasks.

FIG. 44A is a schematic block diagram of an embodiment of a dispersedstorage network (DSN) that includes the distributed storage and tasknetwork (DSTN) managing unit 18 of FIG. 1, the network 24 of FIG. 1, anda dispersed storage network (DSN) memory 416. The DSN memory 416includes a plurality of storage units 418. Each storage unit 418 may beimplemented using one or more of a storage server, a memory array, a DSstorage unit, and the DST execution unit 36 of FIG. 1. Each storage unit418 includes a plurality of memories 88 of FIG. 3.

The system functions to assign operation within the DSN to a set ofstorage units 418 of the plurality of storage units. The DSTN managingunit 18 performs a series of steps to assign the operation of the set ofstorage units. In an example of operation, the DSTN managing unit 18obtains storage requirements. The storage requirements includes one ormore of a storage availability requirement, a retrieval reliabilityrequirement, and a storage efficiency requirement. The obtainingincludes at least one of initiating a query, receiving the storagerequirements, performing a lookup, determining the storage requirementsbased on user input, receiving a storage request, and receiving an errormessage.

The DSTN managing unit 18 obtains resource availability information 420for the plurality of storage units 418. The resource availabilityinformation 420 includes one or more of a storage capacity level, astorage utilization level, a number of memory devices within a storageunit, a number of active memory devices, capacity of each memory device,utilization of each memory device, and an input/output bandwidthcapacity level. The obtaining includes at least one of initiating aquery, receiving a response that includes the resource availabilityinformation 420, performing a lookup, and receiving an error message.

The DSTN managing unit 18 determines dispersal parameters based on thestorage requirements and the resource availability information 420. Forexample, the DSTN managing unit 18 generates a pillar width of thedispersal parameters to be less than or equal to a number of storageunits that are available and will substantially meet the storagerequirements. As another example, the DSTN managing unit 18 generates adecode threshold number of the dispersal parameters based on thegenerated pillar width and the storage requirements (e.g., to achievethe retrieval reliability requirement). As yet another example, the DSTNmanaging unit 18 generates a write threshold number of the dispersalparameters based on one or more of the pillar width, the decodethreshold, and the storage requirements (e.g., to achieve the storageavailability requirement).

The DSTN managing unit 18 selects the set of storage units based on thedispersal parameters and the resource availability information 420. Forexample, the DSTN managing unit 18 identifies storage units associatedwith resource availability information compatible with the storagerequirements and the dispersal parameters. For instance, the DSTNmanaging unit selects 16 storage units associated with favorableresource availability information when the pillar width is 16.

The DSTN managing unit 18 assigns a DSN address range to the set ofstorage units. The assigning includes at least one of identifying a DSNaddress range from a to be assigned address range list, receiving arequest, identifying a requirement for a new generation of a previousgeneration of a vault, identifying a new vault, and identifying anavailable DSN address range based on previously assigned DSN addressranges. The DSTN managing unit 18 may assign one or more memories 88 ofeach storage unit 418 of the selected set of storage units to sub-DSNaddress ranges of the assigned DSN address range to produce addressinginformation based on the resource availability information in thestorage requirements. Alternatively, each storage unit assigns one ormore memories of the storage unit. The selecting includes selectingenough memories to meet a projected storage capacity goal for anassociated vault of the assigned DSN address range.

The DSTN managing unit 18 generates resource assignment information 422to include one or more of the dispersal parameters, identifiers of theset of storage units, the assigned DSN address range, and the addressinginformation. The DSTN managing unit 18 outputs the resource assignmentinformation 422 to each storage unit of the set of storage units toinitialize utilization of the set of storage units for storage of setsof encoded data slices. The outputting includes sending the resourceassignment information 422 directly to the set of storage units andsending the resource assignment information 422 via the DSTN managingunit 18 for redistribution as registry information to numerous DSNentities including the set of storage units.

FIG. 44B is a flowchart illustrating an example of assigning storageresources. The method begins with step 424 where a processing module(e.g., of a distributed storage and task network (DSTN) managing unit)obtains storage requirements. The method continues at step 426 where theprocessing module obtains resource availability information for aplurality of underutilized storage units associated with a dispersedstorage network (DSN) memory. The method continues at step 428 where theprocessing module determines dispersal parameters for a new set ofdispersed storage units based on the storage requirements and theresource availability information. For example, the processing moduledetermines the dispersal parameters to achieve a meantime to data lossgoal and/or a write availability goal.

The method continues at step 430 where the processing module selectsstorage units of the plurality of underutilized storage units to formthe new set of dispersed storage units. The selecting the storage unitsmay be based on the dispersal parameters and the resource availabilityinformation such that operation of the new set of dispersed storageunits substantially achieves the storage requirements. The methodcontinues at step 432 where the processing module assigns a DSN addressrange to the new set of dispersed storage units.

The method continues at step 434 where the processing module selects oneor more memories of each of the underutilized storage units of the newset of dispersed storage units. The method continues at step 436 wherethe processing module allocates sub-DSN address ranges of the DSNaddress range to a set of memories of one or more memories of each ofthe underutilized storage units of the new set of dispersed storageunits to produce addressing information. For example, the processingmodule divides a DSN address range for a storage unit by a number ofavailable memories for the dispersed storage unit to produce the sub-DSNaddress ranges for the dispersed storage unit.

The method continues at step 438 where the processing module generatesresource assignment information to include one or more of the dispersalparameters, identifiers of the new set of dispersed storage units, theassigned DSN address range, and the addressing information. The methodcontinues at step 440 where the processing module outputs the resourceassignment information to the new set of dispersed storage units toinitialize utilization of the new set of dispersed storage units forstorage of sets of encoded data slices associated with the DSN addressrange.

FIGS. 45A, 45B, and 45G are schematic block diagrams of otherembodiments of a dispersed storage network (DSN) illustrating examplesof storing data. The DSN includes the distributed storage and task (DST)processing unit 16 of FIG. 1, the network 24 of FIG. 1, and a DSTexecution unit set 350. The DST execution unit set 350 includes a set ofDST execution units 1-8. Alternatively, the DST execution unit set 350may include any number of DST execution units. Hereafter, the DSTexecution unit may be referred to interchangeably as a storage unit of aset of storage units. Each DST execution unit may be implementedutilizing the DST execution unit 36 of FIG. 1. The DST processing unit16 includes the DST client module 34 of FIG. 1. The DST client module 34includes at least one memory such that the at least one memory storesone or more of a write queue 450 and a rebuild queue 452.

In another embodiment, the DST client module 34 may further includes adispersed storage (DS) module. The DS module may be implementedutilizing a plurality of processing modules. For instance, the pluralityof processing modules may include the processing module 84 of FIG. 3. Asa specific example, the plurality of processing module includes a firstmodule, a second module, a third module, a fourth module, a fifthmodule, and a sixth module.

The DSN functions to store data 454 in the DST execution unit set 350.In an example of operation, DST client module 34 partitions the data 454to produce a plurality of data segments. The DST client module 34dispersed storage error encodes each data segment into a set of encodeddata slices. Each set of encoded data slices includes a total number ofencoded data slices, where a threshold number (e.g., a decode thresholdnumber) of encoded data slices is needed to recover the data segment.The threshold number is less than the total number.

As such, successful storage of each of the total number of encoded dataslices for the set of encoded data slices may provide improved dataretrieval reliability. For example, a highest level of data retrievalreliability is associated with storage of the total number of encodeddata slices and a lowest level of data retrieval reliability isassociated with storage of the threshold number of encoded data slices.Many factors may affect the successful storage of the total number ofencoded data slices, including one or more of network reliability, DSTexecution unit availability, and DST execution unit loading.

The storing of the data includes at least two phases. The at least twophases include a write phase and a commit phase. For example, thestorage of the data includes, for each encoded data slice, the DSTclient module 34 issuing a write command to a corresponding DSTexecution unit and issuing a write commit command to the correspondingDST execution unit when a commit phase trigger has been detected whichincludes receiving a favorable write response in response to the writecommand. As such, the many factors that affect the successful storagemay impact the issuing of the write command, the receiving of thefavorable write response, and the issuing of the write commit command.

The detecting of the commit phase trigger includes receiving favorablewrite responses for the set of encoded data slices within a desiredtiming profile. The desired timing profile includes receiving a numberof favorable write responses within a desired time frame. As such, themany factors that affect the successful storage may impact whether thefavorable write responses are received within the desired time frame.For example, when 8 favorable write responses have been received withinthe desired time frame, the DST client module 34 issues 8 write commitcommands to complete the successful storage of all 8 encoded dataslices.

As another example, once a threshold number (e.g., 5) of favorable writeresponses have been received, the DST client module 34 may issuecorresponding write commit commands at any time but improved retrievalreliability is provided when waiting for a full set of 8 favorable writeresponses. While waiting longer for all 8 of the favorable writeresponses, the longer the storage of the data will take. A systemimprovement may be provided when a balance is struck between anundesired long period of time to store the data and the data retrievalreliability level. For instance, the DST client module 34 issues 6corresponding write commit commands after receiving 6 favorable writeresponses when a response timeframe has expired while waiting for a 7thfavorable write response. The receiving of the favorable write responsesto detect the commit phase trigger is discussed in greater detail withreference to FIGS. 45C-F.

FIG. 45A illustrates initial steps of the example of the storing of thedata. Having produced the set of encoded data slices 1-8, the DST clientmodule 34 caches the set of encoded data slices 1-8 in the write queue450. Having cached the set of encoded data slices 1-8, the DST clientmodule 34 transmits, via the network 24 at time t0, a set of write slicerequests 1-8 as write commands for storing the set of encoded dataslices in the set of DST execution units 1-8.

FIG. 45B illustrates further steps of the example of the storing of thedata, where at least some of the DST execution units temporarily storeencoded data slices extracted from received write slice requests. As aspecific example, the DST execution unit 1 stores encoded data slice 1in a local memory of the DST execution unit 1, DST execution unit 3stores encoded data slice 3, DST execution unit 4 stores encoded dataslice 4, DST execution unit 5 stores encoded data slice 5, DST executionunit 7 stores encoded data slice 7, and DST execution unit 8 storesencoded data slice 8. The many factors that prevent the successfulstorage of the data may prevent the storing of some of the encoded dataslices for storage. As a specific example, one or more storage errorsprevents storage of encoded data slices 2 and 6 within a timeframet7max.

The DST execution units associated with the successful temporary storageof encoded data slices issue favorable write responses to the DST clientmodule 34. For example, DST execution unit 1 sends, via the network 24,a favorable write slice response 1 indicating that the encoded dataslice 1 has been temporarily stored in the DST execution unit 1, DSTexecution unit 3 sends, via the network 24, a favorable write sliceresponse 3 indicating that the encoded data slice 3 has been temporarilystored in the DST execution unit 3, etc.

The DST client module 34 receives write slice responses from the DSTexecution unit set 350. As a specific example, the DST client module 34receives, via the network 24, write slice responses 1, 3, 4, 5, 7, 8 attime t7max, where each of the write slice responses indicates that thecorresponding encoded data slice has been successfully temporarilystored. Having received the write responses, the DST client module 34determines whether at least a first threshold number of the writeresponses have been received within a first response time period. Forexample, the DST client module 34 determines whether five writeresponses have been received within a time period of t5max, where t5maxis a maximum amount of time from t0 allowed to receive the firstthreshold number of the write responses in accordance with the desiredtiming profile. The desired timing profile is discussed in greaterdetail with reference to FIGS. 45C-F.

FIGS. 45C, 45D, 45E, and 45F are timing diagrams illustrating examplesof establishing response time periods of the desired timing profile. Theestablishing of the response time periods includes one of a desiredtiming profile based on a predetermination of maximum allowed timeframes for each incremental received write response and a dynamicdetermination of a next allowed time frame for each incremental receivedwrite response. FIGS. 45C and 45D illustrate examples of establishingthe response time periods based on the predetermination of the maximumallowed time frames for each incremental received write response. FIGS.45E and 45F illustrates examples of establishing response time periodsbased on the dynamic determination of the next allowed time frame foreach incremental received write response. Each example indicates anumber of favorable slice responses 456 received over time 458, whereone or more maximum time frames are associated with the receiving of thewrite responses when the first threshold number includes the decodethreshold number 460, and where the total number is 8 and the decodethreshold number is 5.

FIG. 45C illustrates a first example of the establishing of the responsetime periods, where the first threshold number of 5 write responses arereceived at t5, where t5 is less than an allowable t5max in accordancewith the desired timing profile where the first response time period ispre-established. As such, when the DST client module 34 of FIG. 45Bdetermines whether the at least a first threshold number of 5 writeresponses have been received within the first response time periodt5max, the DST client module 34 indicates that the first thresholdnumber have been received within the first response time period.Alternatively, when the at least the first threshold number of the writeresponses have not been received within the first response time period,the DST client module 34 indicates a write failure.

When the at least the first threshold number of the write responses havebeen received within the first response time period and the at least thefirst threshold number is equal to the total number, the DST clientmodule 34 issues a set of write commit commands corresponding to the setof encoded data slices. When the at least the first threshold number ofthe write responses have been received within the first response timeperiod and the at least the first threshold number is less than thetotal number, the DST client module 34 determines whether at least asecond threshold number of the write responses have been received withina second response time period, where the first threshold number is lessthan the second threshold number and where the second response timeperiod is subsequent to the first response time period. The secondresponse time period may be pre-established. For example, the DST clientmodule 34 determines whether a sixth write response has been receivedbefore t6max. As another example, the DST client module 34 determineswhether a seventh write response has been received before t7max. As yetanother example, the DST client module 34 determines whether an eighthwrite response has been received before t8max.

When the at least the second threshold number of the write responseshave been received within the second response time period and the atleast the second threshold number is equal to the total number, the DSTclient module 34 issues the set of write commit commands correspondingto the set of encoded data slices. When the at least the secondthreshold number of the responses have been received within the secondresponse time period and the at least the second threshold number isless than the total number, the DST client module 34 determines whetherthe total number of responses have been received within a third responsetime period, where the second threshold number is less than the totalnumber and where the third response time period is subsequent to thesecond response time period and the third response time period ispre-established. For example, the DST client module 34 determineswhether the seventh write response has been received before t7max. Asanother example, the DST client module 34 determines whether the eighthwrite response has been received before t8max.

When the total number of responses have been received within the thirdresponse time period, the DST client module 34 issues the set of writecommit commands corresponding to the set of encoded data slices. Forexample, the DST client module 34 issues 8 write commit commands to theset of storage units when eight write responses have been received att8, where t8 is less than t8max of the desired timing profile.

Alternatively, or in addition to, prior to expiration of the thirdresponse time period, the DST client module 34 determines whether atleast a fourth threshold number of responses have been received within afourth response time period, where the fourth threshold number is lessthan the total number and wherein the fourth response time period is aportion of the third response time period and is subsequent to thesecond response time period. For example, the DST client module 34determines whether an eighth write response has been received withint8max.

When the at least the fourth threshold number of the responses have beenreceived within the fourth response time period and the at least thefourth threshold number is less than the total number, the DST clientmodule 34 determines whether the total number of responses have beenreceived within the third response time period. For example, the DSTclient module 34 determines that the total number of responses have beenreceived when the eighth write response has been received at t8 and t8is less than t8max.

FIG. 45D illustrates a second example of the establishing of theresponse time periods. When the at least the first threshold of thewrite responses have been received within the first response time period(e.g., t5<t5max) and the at least the second threshold number of thewrite responses have been received within the second response timeperiod (e.g., t6<t6max), the DST client module 34 determines whether thetotal number of responses have been received within the third responsetime period (t8 within t8max). When the total number of responses havenot been received within the third response time period, the DST clientmodule 34 issues a sub-set of write commit commands (e.g., 6 writecommit requests) to associated storage units corresponding to a responsenumber of encoded data slices for which a response was received, wherethe response number is less than the total number and is equal to orgreater than the at least the second threshold number.

Alternatively, when the at least the first threshold of the writeresponses have been received and the at least the second thresholdnumber of the write responses have not been received within the secondresponse time period (e.g., if t6>t6max), the DST client module 34issues a second sub-set of 5 write commit commands corresponding to asecond response number (e.g., 5) of encoded data slices for which theresponse was received prior to the expiration of the second responsetime period.

FIG. 45E illustrates a third example of the establishing of the responsetime periods that includes three steps corresponding to receiving writeresponses for encoded data slices 6-8. In a first step for receiving theencoded data slice 6, the DST client module 34 receives the at least thefirst threshold number of write responses within the first response timeperiod. For instance, the DST client module 34 receives five writeresponses by t5 prior to t5max. Having received the first threshold ofthe write responses within the first response time period, the DSTclient module 34 determines the second response time period based on thefirst response time period and the receiving of the at least the firstthreshold number of write responses. For example, the DST client module34 determines t6max to achieve a balance in storage time and dataretrieval reliability level. The DST client module 34 receives the sixthwrite response at t6 prior to t6max.

In a second step for receiving the encoded data slice 7, the DST clientmodule 34 determines the third response time period based on based onthe receiving of the at least the second threshold number of writeresponses. For example, the DST client module 34 determines t7max toachieve the balance in storage time and data retrieval reliabilitylevel. The DST client module 34 receives the seventh write response att7 prior to t7max.

In a third step for receiving the encoded data slice 8, the DST clientmodule 34 determines a fourth response time period based on based on thereceiving of the at least the third threshold number of write responses.For example, the DST client module 34 determines t8max to achieve thebalance in storage time and data retrieval reliability level. The DSTclient module 34 receives the eighth write response at t8 prior tot8max. When receiving the total number of write responses within thefourth response time period, the DST client module 34 issues the set ofwrite commit commands to the set of storage units. For example, the DSTclient module 34 issues eight write commit commands to the set ofstorage units.

FIG. 45F illustrates a fourth example of the establishing of theresponse time periods that includes two steps corresponding to receivingwrite responses for encoded data slices 6-7. In a first step forreceiving the encoded data slice 6, the DST client module 34 receivesthe at least the first threshold number of write responses within thefirst response time period. For instance, the DST client module 34receives five write responses by t5 prior to t5max. Having received thefirst threshold of the write responses within the first response timeperiod, the DST client module 34 determines the second response timeperiod based on the first response time period and the receiving of theat least the first threshold number of write responses. For example, theDST client module 34 determines t6max to achieve a balance in storagetime and data retrieval reliability level. The DST client module 34receives the sixth write response at t6 prior to t6max.

In a second step for receiving the encoded data slice 7, the DST clientmodule 34 determines the third response time period based on thereceiving of the at least the second threshold number of writeresponses. For example, the DST client module 34 determines t7max toachieve the balance in storage time and data retrieval reliabilitylevel. The DST client module 34 does not receive the seventh writeresponse at t7 prior to t7max. When the total number of write responseshave not been received within the third response time period, the DSTclient module 34 issues a sub-set of write commit commands correspondingto a response number of encoded data slices for which a write responsewas received, where the response number is less than the total numberand is equal to or greater than the at least the second thresholdnumber. For example, the DST client module 34 issues 6 write commitcommands to corresponding storage units when not receiving the totalnumber of write responses by t7max.

FIG. 45G illustrates final steps of the example of the storing of thedata. When the total number of write responses have not been receivedwithin the third response time period, the DST client module 34 issues asub-set of write commit commands corresponding to a response number ofencoded data slices for which a write response was received, where theresponse number is less than the total number and is equal to or greaterthan the at least the second threshold number. For example, the DSTclient module 34 sends, via the network 24 at a time subsequent to t7,write commit requests 1, 3, 4, 5, 7, and 8 as write commands to the DSTexecution units 1, 3, 4, 5, 7, and 8 to commit encoded data slices 1, 3,4, 5, 7, and 8. Each of the DST execution units 1, 3, 4, 5, 7, and 8changes status of the temporarily stored encoded data slices 1, 3, 4, 5,7, and 8 to non-temporarily stored and makes available the encoded dataslices 1, 3, 4, 5, 7, and 8 for retrieval. The DST client module 34identifies remaining encoded data slices of the set of encoded dataslices for rebuilding. The DST client module 34 stores identities of theencoded data slices identified for rebuilding in the rebuild queue 452.For example, the DST client module identifies encoded data slices 2 and6 and stores identities of encoded data slices 2 and 6 in the rebuildqueue 452.

The storing of the data may include further phases. For example, the DSTclient module 34 issues write finalize commands to DST execution units1, 3, 4, 5, 7, and 8 when subsequently receiving favorable write commitresponses in accordance with the desired timing profile. When issuingthe write finalize commands, the DST client module 34 may delete theencoded data slices 1, 3, 4, 5, 7, and 8 from the write queue 452 toconclude the storing of the data.

FIG. 45H is a flowchart illustrating an example of storing data. Themethod begins at step 462 where a processing module (e.g., a distributedstorage and task processing module of a dispersed storage network (DSN))transmits a set of write commands for storing a set of encoded dataslices in storage units of the DSN, wherein a data segment is dispersedstorage error encoded into the set of encoded data slices. The set ofencoded data slices includes a total number of encoded data slices. Athreshold number of encoded data slices is needed to recover the datasegment. The threshold number is less than the total number.

The method continues at step 464 where the processing module determineswhether at least a first threshold number of write responses have beenreceived within a first response time period. The determining mayinclude the processing module pre-establishing the first response timeperiod. Alternatively, the processing module dynamically establishes thefirst response time period. The method continues to step 470 when the atleast the first threshold number of write responses have been receivedwithin the first response time period and the at least the firstthreshold number is not equal to the total number. The method branchesto step 468 when the at least the first threshold number of writeresponses have been received within the first response time period andthe at least the first threshold number is equal to the total number.The method branches to step 466 when the at least the first thresholdnumber of write responses have not been received within the firstresponse time period.

When the at least the first threshold number of the write responses havenot been received within the first response time period, the methodcontinues at step 466 where the processing module indicates a writefailure. For example, the processing module outputs a write failuremessage to at least one of a requesting entity and a managing entity.When the at least the first threshold number of the write responses havebeen received within the first response time period and the at least thefirst threshold number is equal to the total number, the methodcontinues at step 468 where the processing module issues a set of writecommit commands corresponding to the set of encoded data slices.

When the at least the first threshold number of the write responses havebeen received within the first response time period and the at least thefirst threshold number is less than the total number, the methodcontinues at step 470 where the processing module determines whether atleast a second threshold number of the write responses have beenreceived within a second response time period, where the first thresholdnumber is less than the second threshold number and where the secondresponse time period is subsequent to the first response time period.The determining may include the processing module pre-establishing thesecond response time period. Alternatively, the processing moduledynamically establishes the second response time period. Whendynamically establishing the second response time period, the processingmodule determines the second response time period based on the firstresponse time period and the receiving of the at least the firstthreshold number of responses.

The pre-establishing and the establishing of the second response timeperiod may include determining cost information. The cost informationincludes a cost of not waiting for additional favorable write responsesand a cost of waiting for one or more additional favorable writeresponses. The cost of not waiting includes one or more of incrementalcosts associated with losing data based on an estimated reliabilitylevel utilizing encoded data slices favorably written so far, networkbandwidth costs due to rebuilding one or more unwritten slices later,and storage unit costs associated with rebuilding the one or moreunwritten slices later. As a specific example, the processing modulemultiplies a cost of losing data by a difference of a probability ofdata loss implied by not writing an encoded data slice and a probabilityof data loss implied by writing the encoded data slice.

The cost of waiting includes one or more of a cost associated with anestimated amount of time to wait before determining to commit storage ofthe set of encoded data slices, a cost associated with a forecasted timeto commit the storage versus a planned time to commit the storage, and acost associated with lowered perceived system performance at a userdevice with regards to subsequently accessing the set of encoded dataslices. As a specific example, the processing module calculates a costassociated with a difference between the forecasted time to commit thestorage and an original storage deadline plan.

Having determined the cost information, the processing module determinesthe second time period (e.g., and similarly a possible third or moretime periods) to enable commitment of storage of the set of encoded dataslices based on the cost information. For example, the processing moduleestablishes a shorter than average second time period to enable thecommitment of the storage when the cost of waiting is greater than thecost of not waiting. As a specific example, the processing moduledetermines to not wait any further after receiving at least a decodethreshold number of favorable write responses to commit storage when thecost of waiting far outweighs the cost of not waiting (e.g., rebuildingcosts are low). As another specific example, the processing moduleindicates to wait to commit storage until at least the second number ofwrite responses have been received when the cost of not waiting isgreater than the cost of waiting (e.g., slower/lowered performance costis low).

The method branches to step 472 when the at least the second thresholdnumber of write responses have not been received within the secondresponse time period. The method branches to step 474 when the at leastthe second threshold number of write responses have been received withinthe second response time period and the at least the second thresholdnumber is equal to the total number. The method continues to step 476when the at least the second threshold number of write responses havebeen received within the second response time period and the at leastthe second threshold number is not equal to the total number.

When the at least the second threshold number of the write responseshave not been received within the second response time period, themethod continues at step 472 where the processing module issues a secondsub-set of write commit commands corresponding to a second responsenumber of encoded data slices for which the response was received priorto the expiration of the second response time period. When the at leastthe second threshold number of the write responses have been receivedwithin the second response time period and the at least the secondthreshold number is equal to the total number, the method continues atstep 474 where the processing module issues a set of write commitcommands corresponding to the set of encoded data slices.

When the at least the second threshold number of the write responseshave been received within the second response time period and the atleast the second threshold number is less than the total number, themethod continues at step 476 where the processing module determineswhether the total number of write responses have been received within athird response time period, where the second threshold number is lessthan the total number and where the third response time period issubsequent to the second response time period. The determining mayinclude the processing module pre-establishing the third response timeperiod. Alternatively, the processing module dynamically establishes thethird response time period. When the processing module dynamicallyestablishes the third response time period, the processing moduledetermines the third response time period based on the receiving of theat least the second threshold number of responses.

When the total number of responses have been received within the thirdresponse time period, the method branches to step 478. When the totalnumber of write responses have not been received within the thirdresponse time period, the method continues to step 480. When the totalnumber of responses have been received within the third response timeperiod, the method continues at step 478 where the processing moduleissues a set of write commit commands corresponding to the set ofencoded data slices.

When the total number of write responses have not been received withinthe third response time period, the method continues at step 480 wherethe processing module issues a sub-set of write commit commandscorresponding to a response number of encoded data slices for which aresponse was received, where the response number is less than the totalnumber and is equal to or greater than the at least the second thresholdnumber. Alternatively, or in addition to, prior to expiration of thethird response time period, the processing module determines whether atleast a fourth threshold number of responses have been received within afourth response time period, wherein the fourth threshold number is lessthan the total number and wherein the fourth response time period is aportion of the third response time period and is subsequent to thesecond response time period. When the at least the fourth thresholdnumber of the responses have been received within the fourth responsetime period and the at least the fourth threshold number is less thanthe total number, the processing module determines whether the totalnumber of responses have been received within the third response timeperiod.

FIG. 46A is a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes a rebuilding module 490, astorage module 492, and a storage unit set 494. The rebuilding module490 may be implemented utilizing the distributed storage and task (DST)integrity processing unit 20 of FIG. 1. The storage module 492 may beimplemented utilizing the DST processing unit 16 of FIG. 1. The storageunit set 494 includes a set of storage units 418 of FIG. 44A.

The DSN functions to prioritize rebuilding data. The storage units 418store sets of encoded data slices associated with data and may receiverebuild requests 498 to rebuild at least some encoded data slices andmay receive storage requests 506 to access the encoded data slices. Eachstorage unit 418 may not have enough processing capability to process atotality of the rebuild requests 498 and the storage requests 506 withindesired time frames. The storage unit 418 utilizes a task prioritizationalgorithm to prioritize the totality of the rebuild requests 498 and thestorage requests 506. The rebuilding module 490 collects data lossinformation 496 and storage error information 500, generates arebuilding rate 502, generates a data loss rate 504, and shares therates of rebuilding and data loss with the storage unit set 494. Thestorage unit 418 executes the task prioritization algorithm based on therates of rebuilding and data loss to perform the task prioritizationalgorithm.

The rebuild request 498 includes at least one of a request to rebuild anencoded data slice, a slice name, a request for a partially encodedslice, a request to scan a slice for error, and a request to retrieve aslice for a rebuild operation. The storage request 506 includes a writeslice request that includes a slice name and an encoded data slice. Thestorage unit 418 may issue a storage response 508 that includes a writeslice response indicating success or failure of executing a write slicerequest of a corresponding storage request 506. The data lossinformation 496 includes a rate of data loss due to slice errors (e.g.,missing encoded data slice, corrupted encoded data slice, a memoryfailure). The storage error information 500 includes a data loss ratedue to data being written but not stored. For instance, a rate of datawritten when a storage unit was off line. The rate of rebuildingincludes an aggregated rate at which encoded data slices are rebuiltfollowing error detection. The data loss rate includes a rate based onthe data loss information 496 and the storage error information 500indicating how much data is lost per unit of time.

In an example of operation, the rebuilding module 490 receives the dataloss information 496 from one or more storage units 418. The rebuildingmodule 490 issues rebuild requests 498 to storage units 418 when thedata loss information 496 indicates at least one slice error. Therebuilding module 490 receives storage error information 500 from thestorage module 492 when errors associated with storage of one or moreencoded data slices occurs. As a specific example, the storage module492 issues a set of storage requests 506 to the set of storage units 418and receives favorable storage responses 508 from all storage units butone storage unit 418. The storage module 492 then generates the storageerror information 500 to indicate that a corresponding encoded dataslice of the one storage unit 418 is associated with a slice storageerror. The rebuilding module 490 generates the rebuild rate 502 based ona rate of rebuilding associated with the rebuild requests 498. Therebuilding module 490 generates the data loss rate 504 based on the dataloss information 496 and the storage error information 500. Therebuilding module 490 sends the rebuild rate 502 and data loss rate 504to the storage unit set 494.

In another example of operation, each storage unit 418 receives therebuild rate 502 and the data loss rate 504. Each storage unit 418prioritizes received storage requests 506 and received rebuild requests498 based on the rebuild rate 502 and the data loss rate 504. As aspecific example, the storage unit 418 prioritizes the rebuild requests498 over the storage requests 506 when the rebuild rate 502 comparesunfavorably to the data loss rate 504. For instance, when the rebuildrate 502 is less than the data loss rate 504. As another instance, whenthe rebuild rate 502 is greater than the data loss rate 504 and adifference between the rebuild rate 502 and the data loss rate 504 isless than a low threshold. As another specific example of the storageunit prioritizing the received storage requests 506 and the receivedrebuild requests 498, the storage unit 418 prioritizes the storagerequests 506 over the rebuild requests 498 when the rebuild rate 502compares favorably to the data loss rate 504. For instance, when therebuild rate 502 is greater than the data loss rate 504 by more than ahigh threshold level.

FIG. 46B is a flowchart illustrating another example of prioritizingrebuilding data. The method begins with step 510 where a processingmodule (e.g., of a rebuilding module) receives data loss informationfrom a set of storage units. The method continues at step 512 where theprocessing module issues rebuild requests to one or more storage unitsof the set of storage units when a slice error is detected based on thedata loss information. The method continues at step 514 where theprocessing module receives storage error information with regards toerrors associated with storage of one or more encoded data slices to theset of storage units. The method continues at step 516 where theprocessing module generates a rebuild rate based on a rate associatedwith the rebuild requests. The method continues at step 518 where theprocessing module generates a data loss rate based on the data lossinformation and the storage error information. The method continues atstep 520 where the processing module sends the rebuild rate and the dataloss rate to the set of storage units.

The method continues at step 522 where each storage unit of the set ofstorage units obtains the rebuild rate and the data loss rate. Forexample, the storage unit receives the rebuild rate in the data lossrate from the rebuilding module. As another example, the storage unitgenerates at least one of the rebuild rate and the data loss rate. Themethod continues at step 524 where the storage unit prioritizes rebuildrequests over storage requests when the rebuild rate comparesunfavorably to the data loss rate. For example, the storage unit updatesa priority level indicator to prioritize. As another example, thestorage unit reorders a task list placing higher priority tasks ahead ofother tasks. The method continues at step 526 where the storage unitprioritizes storage requests over rebuild requests when the rebuild ratecompares favorably to the data loss rate.

FIG. 47A is a schematic block diagram of an embodiment of a set ofstorage units 418 of FIG. 44A, where each storage unit 418 includes thecontroller 86 of FIG. 3 and the memory 88 of FIG. 3. In an example ofoperation, the controller 86 receives a data slice 530 and slice namefor the data slice and stores the data slice 530 in the memory 88 inaccordance with a current format data 532 associated with the slicename. From time to time, the current format data 532 may be updated suchthat a new current format is to be utilized for subsequent storage offurther received data slices in the memory 88 and the current formatbecomes a previous format data 534. The format includes an internal datastorage format. The internal data storage format includes at least oneof null revision appender (e.g., appended as data grows), file-basedstorage (e.g., fixed or variable block sizes stored that are associatedwith a file name structure), packed storage (e.g., bytes densely filledin), in memory storage (e.g., volatile storage), flash storage (e.g.,non-volatile storage), and any other industry standardized ornon-standardized data storage formats. The format of previously storeddata may be changed from time to time. For example, the format ischanged when migrating storage of metadata of data from the file-basedstorage format to the packed storage format to more efficiently utilizethe memory 88. The controller 86 executes the method of FIG. 47C tochange the format of the previously stored data.

In another example of operation, the controller 86 receives the dataslice 530 for storage and the slice name of the data slice. Thecontroller 86 identifies a slice name range (e.g., a dispersed storagenetwork (DSN) address range) associated with the slice name. As aspecific example, the controller 86 accesses a storage information tablethat includes one or more slice name ranges and identifies the slicename range when the slice name is within the slice name range. Thecontroller 86 identifies a current format and a current memory range forstorage of the data slice based on the slice name range. The memoryrange includes a memory address range within the memory 88 associatedwith the slice name range when storing data slices associated with thecurrent format. As a specific example, the controller 86 extracts thecurrent format in the current memory range from the storage informationtable. The controller 86 stores the data slice in an available storagelocation of memory 88 within the current memory range and in accordancewith the current format data 532. As a specific example, the controller86 sends current format data 532 to the memory 88 to store the dataslice at an open storage location of memory 88 using the file-basedstorage format.

The controller 86 determines to migrate a format of data storage to anew format. For example, the controller 86 detects at least one of aslice error, a storage capacity issue, and a request to migrate formats.Having determined to migrate the format, the controller 86 identifies aslice name range to migrate of the data to migrate (e.g., accessing thestorage information table based on a slice name). The controller 86identifies a current format and current memory range associated with theslice name range to migrate (e.g., accessing the storage informationtable based on the identified slice name range). The controller 86establishes the current format in the current memory range associatedwith a slice name range to migrate as a previous format in a previousmemory range. As a specific example, the controller 86 updates thestorage information table to equate the previous format and previousmemory range to the current format and current memory rangerespectively.

Having saved the now previous format data 534 and previous memory range,the controller 86 updates the current format of the storage informationtable with the new format and selects a new memory range based on theprevious memory range and available memory of the memory 88. Thecontroller 86 updates the current memory range of the storageinformation table to include the new memory range. The controller 86migrates data of the previous memory range by retrieving data of theprevious memory range as previous format data 534, converting the datafrom the previous format to the current format to produce converteddata, and storing the converted data in the current memory range. Whenthe migration is complete, the controller 86 releases previous memoryrange allocations to make the previous memory range available forsubsequent reallocation.

FIG. 47B is a diagram illustrating an example of a structure of astorage information table 536 that includes a slice name range field538, and four other fields associated with the slice name range. Thefour other fields includes a pair of related fields including a previousformat field 540 and a previous memory range field 542. Remaining fieldsof the four other fields includes another pair of related fieldsincluding a current format field 544 and a current memory range field546. The storage information table 536 may be utilized to track internaldata storage formats utilized to store encoded data slices within amemory of a storage unit as discussed with reference to FIG. 47A.

FIG. 47C is a flowchart illustrating an example of migrating dataformats. The method begins with step 548 where a processing module(e.g., of a storage unit) receives a data slice for storage. Theprocessing module receives a slice name associated with the data slice.The method continues at step 550 where the processing module identifiesa slice name range associated with the data slice. For example, theprocessing module compares the slice name to one or more slice nameranges of a storage information table to identify the slice name range.The method continues at step 552 where the processing module identifiesa current format and a current memory range for storage of the dataslice. For example, the processing module extracts the current formatand the current memory range from an entry of the storage informationtable associated with the slice name range. The method continues at step554 where the processing module stores the data slice in an availablestorage location of the current memory range in accordance with thecurrent format. For example, the processing module selects a memorydevice and an address of the memory device associated with the availablestorage location, converts the data slice to data for storage inaccordance with the current format, and stores the converted data at theaddress of the memory device.

The method continues, when migrating data, at step 556 where theprocessing module determines to migrate format of data to migrate to anew format. For example, the processing module determines to migrateformat based on at least one of receiving a request, accessing registryinformation, detecting an error, and detecting a storage capacity issue.As a specific example, the processing module detects that the storageunit is about to run out of available storage space utilizing thecurrent format. The method continues at step 558 where the processingmodule identifies a slice name range(s) to migrate associated with thedata to migrate (e.g., slice name range associated with the data tomigrate). The method continues at step 560 where the processing moduleidentifies a current format and a current memory range associated with aslice name range to migrate (e.g., extract from the storage informationtable). The method continues at step 562 where the processing moduleestablishes the current format and the current memory range associatedwith a slice name range to migrate as a previous format and a previousmemory range (e.g., copy from current to previous in the storageinformation table).

The method continues at step 564 where the processing module updates thecurrent format of the slice name range to migrate as the new format. Themethod continues at step 568 where the processing module selects a newmemory range based on the previous memory range and available memory.For example, the processing module identifies available memory andidentifies unassigned memory addresses within the memory thatsubstantially matches a level of memory utilization of the currentmemory range. The method continues at step 570 where the processingmodule updates the current memory range of the slice name range tomigrate as the new memory range. The method continues at step 572 wherethe processing module migrates data from the previous memory range tothe updated current memory range in accordance with the updated currentformat. For example, the processing module receives previous format datafrom a portion of the previous memory range, converts the portion inaccordance with the updated current format to produce current formatdata, and stores the current format data within a corresponding portionof the updated current memory range. When migration is complete, themethod continues at step 574 where the processing module releasesprevious memory range allocations. For example, the processing moduleindicates that the previous memory range is available for reassignment.

FIGS. 48A-C are diagrams illustrating examples of a series of stepsupdating a dispersed hierarchical index structure that includes aplurality of levels and a plurality of nodes to facilitate efficientlocating of data stored in a dispersed storage network (DSN). One ormore processing modules of the DSN function to update the dispersedhierarchical index structure. A top-level includes a root index node(ROOTNODE) and a bottom level includes one or more leaf nodes(LEAFNODE). The dispersed hierarchical index may further include one ormore middle levels of index nodes (INDXNODE). Nodes in a higher levelabove other nodes at a lower level may serve as parent nodes and theother nodes at the lower-level serve as child nodes to the parent nodes.Nodes at a common level serve as sibling nodes to nodes at the commonlevel. Leaf nodes may include a data object and/or may include a DSNaddress associated with the data object stored as a set of data sliceswithin the DSN. Nodes are encoded using a dispersed storage error codingfunction to produce a set of index slices for storage in the DSN. Thenodes include a DSN address field that points to a storage locationwithin the DSN where associated nodes are stored. For example, the DSNaddress field includes a DSN address associated with a sibling indexnode to the right and another DSN address associated with one or morechild nodes.

The nodes are further associated with a minimum index key value toenable searching the dispersed hierarchical index structure to identifya leaf node that corresponds to a desired data object. The dispersedhierarchical index may be searched using an index key associated with anattribute of a desired search and comparing the index key to minimumindex key values associated with nodes as searching starts with the rootnode and proceeds in a downward direction within the index structure toidentify the leaf node that corresponds to the desired data object. Aseries of retrievals of sets of encoded index slices from the DSN may berequired to recover nodes along a search path from the root node to theleaf node associated with the desired data object. Two or more dispersedhierarchical indexes may include entries within leaf nodes that point toa common data object when two or more attributes of the common dataobject are associated with two or more index keys utilized whensearching the two or more dispersed hierarchical indexes.

The set of index slices of the node may be stored within the DSN at aset of storage units, where each storage unit stores an index slice in amemory of the storage unit in accordance with a data storage format. Thedata storage format may be changed to a new data storage format withineach storage unit requiring conversion of storage of each set of indexslices of all the nodes of the dispersed hierarchical index. The DSN maymaintain registry information that includes an indication of the datastorage format and the new data storage format associated with the setsof index slices. When the registry information indicates that the datastorage format is to be converted to the new data storage format, one ormore processing modules of the DSN function execute a series of steps toupdate (e.g., convert) the storage of the dispersed hierarchical indexfrom the data storage format to the new data storage format asillustrated in FIGS. 48A-C.

FIG. 48A illustrates an example of a first step of the series of stepsto update the dispersed hierarchical index structure. Subsequent toupdating of the registry information, the root node is recovered fromthe DSN and deletion of the root node is initiated (e.g., issue deleteslice requests). A new root node (NEWROOTNODE) is generated using theroot node (e.g., copy root node to the new root node). The root node isencoded using the dispersed storage error coding function to produce aset of new root node slices. Storage of the new root node, using the newformat, is initiated within the DSN by generating a set of write slicerequests that includes the set of new root node slices and sending thenew root node slices to a new DSN address associated with the dispersedhierarchical index (e.g., as indicated by the registry information, asmaintained in a table). The set of storage units, being updated with thenew registry information, utilizes the new format when storing the setof new root node slices. The storage of the new root node and deletionof the root node is completed by issuing commit transaction requestswith regards to the storage of the new root node and the deletion of theroot node. For example, a first set of commit transaction requests isgenerated to include a transaction number of the delete root noderequests and another set of commit transaction requests is generated toinclude a transaction number of the write slice requests of the set ofnew root node slices.

FIG. 48B illustrates an example of a second step of the series of stepsto update the dispersed hierarchical index structure. Having created andconnected the new root node to the dispersed hierarchical index, foreach leaf node, a node split operation is performed which includesgenerating a new leaf node (NEWLEAFNODE) to include all data of the leafnode and storing the new leaf note (e.g., each storage unit utilizes thenew format), updating pointers in parent nodes to point to the new leafnodes (e.g. and not to the leaf nodes), and updating pointers withinsibling leaf nodes to the left to point to the new leaf node and not tothe leaf node. Next, the leaf node may be deleted by issuing delete leafnode slice requests to the set of storage units.

FIG. 48C illustrates an example of a third step of the series of stepsto update the dispersed hierarchical index structure. Having updated thelowest level of the index structure to include new leaf nodes, eachindex node of the one or more middle levels of index nodes is replacedwith a new index node (NEWINDEXNODE). The replacing includes, for eachindex node, a node split operation which includes generating the newindex node to include all data of the index node and storing the newindex node (e.g., each storage unit uses the new format), updatingpointers in parent nodes to point to the new index nodes, and updatingpointers within sibling index nodes to the left to point to the newindex node and not to the index node. Next, the index nodes may bedeleted by issuing delete index node slice requests to the set ofstorage units.

FIG. 48D is a flowchart illustrating an example of migrating nodes of adispersed hierarchical index to a new data format. The method beginswith step 576 where a processing module (e.g., of a distributed storageand task (DST) client module) recovers a root node of a dispersedhierarchical index from a dispersed storage network (DSN). For example,the processing module obtains a DSN address for the root node (e.g.,lookup, receive), generates read slice requests based on the DSNaddress, sends the read slice requests to a set of storage units of theDSN, receives slices from at least a decode threshold number of thestorage units, and decodes the received slices using a dispersed storageerror coding function to reproduce the root node. The method continuesat step 578 where the processing module initiates deletion of the rootnode. For example, the processing module outputs a set of delete slicerequests based on the DSN address of the root node. The method continuesat step 580 where the processing module generates a new root node toinclude the root node (e.g. copy).

The method continues at step 582 where the processing module initiatesstorage of the new root node in the DSN utilizing a new storage format.For example, the processing module obtains a new DSN address of the newroot node, encodes the new root node using the dispersed storage errorcoding function to produce a set of new root node slices, and outputsthe set of new root node slices to the set of storage units for storage.The method continues at step 584 where the processing module completesstorage of the new root node and deletion of the root node. For example,the processing module issues at least one set of commit transactionrequests that includes a transaction number associated with deletion ofthe root node and a transaction number associated with initiatingstorage of the new root node.

For each leaf node of a leaf node level of the dispersed hierarchicalindex, the method continues at step 586 where the processing moduleperforms a leaf node split operation to replace the leaf node with a newleaf node. For example, the processing module generates the new leafnode to include all data of the leaf node and stores the new leaf nodewith a new leaf node DSN address, updates pointers in parent nodes topoint to the new leaf node and not to the leaf node, updates pointers ofsibling leaf nodes to the left to point to the new leaf node and not tothe leaf node, and deletes the leaf node.

For each index node of each index node level of the dispersedhierarchical index, the method continues at step 588 where theprocessing module performs an index node split operation to replace theindex node with a new index node. For example, the processing modulestarts with an index node of a lowest index node level and generates anew index node to include all data of the index node, stores the newindex node at a new DSN address in the set of storage units, updatespointers in parent nodes to point to the new index nodes and not to theindex nodes, updates pointers of sibling index nodes to the left topoint to the new index node and not to the index node, and deletes theindex nodes.

FIG. 49A is a schematic block diagram of another embodiment of adistributed computing system that includes the user device 12 of FIG. 1,the DST processing unit 16 of FIG. 1, the user device 14 of FIG. 1, theDST integrity processing unit 20 of FIG. 1, the DSTN module 22 of FIG.1, the network 24 of FIG. 1, and the DSTN managing unit 18 of FIG. 1.The user device 12 and the DST processing unit 16 includes the DSTclient module 34 of FIG. 1. The DSTN module 22 includes the plurality ofDST execution units 36 of FIG. 1. The DSTN managing unit 18 updatesentities of the distributed computing system with regards to registryinformation 590, where the registry information identifies storageformats utilized by the DST execution units 36 for storage vaults. Astorage vault includes an association of one or more of a group of userdevices, the group of data objects for storage, a time span of storage,and any other affiliation. The DSTN managing unit 18 updates theentities of the distributed computing system using an updating orderingto facilitate concurrency of data and continuous data access while theDSTN managing unit 18 performs the updating.

In an example of operation, the DSTN managing unit 18 generates newvaults associated with data storage utilizing a new storage format,where the new vaults correspond to old vaults utilizing a previousstorage format. The DSTN managing unit 18 evokes the generating of thenew vaults based on one or more of receiving a manager input, detectinga storage issue within the DSTN module 22, forecasting a futurepotential storage issue within the DSTN module, and receiving a request.The DSTN managing unit 18 generates updated registry information 590with regards to the new vaults indicating an association with the oldvaults. The DSTN managing unit 18 first sends the registry information590 that has been updated to the DST execution units 36 and to the DSTintegrity processing unit 20 when the corresponding DST execution unit36 and DST integrity processing unit 20 is associated with a DSN addressrange assignment that corresponds to the old vaults.

Next, the DSTN managing unit 18 sends the registry information 590 tothe user device 12 when the user device 12 is also associated with theDSN address range assignments that correspond to the old vaults. Then,the DSTN managing unit sends the registry information 590 to the DSTprocessing unit 16 when the DS processing unit 16 is also associatedwith the DSN address range assignments that correspond to the oldvaults. Next, the DSTN managing unit 18 suspends operation of the oldvaults by issuing further updated registry information 590 to all DSNentities that are associated with the DSN address range of the oldvaults, where the further updated registry information 590 indicatesthat the old vaults have been replaced by the new vaults. Henceforth,each DSN entity utilizes the new vaults and suspends operations with theold vaults.

FIG. 49B is a flowchart illustrating an example of updating a storageformat. The method begins with step 592 where a processing module (e.g.,of the DSTN managing unit 18 of FIG. 49A) generates new vaultsassociated with data storage using a new format, where the new vaultscorrespond to old vaults utilizing a previous format. The methodcontinues at step 594 where the processing module generates registryinformation with regards to the new vaults and in association with oldvaults.

The method continues at step 596 where the processing module outputs theregistry information to storage units associated with the old vaults.For example, the processing module identifies the storage units based ona mapping of the old vaults to DSN address range assignments to thestorage units. The method continues at step 598 where the processingmodule outputs the registry information to one or more user devicesassociated with the old vaults. For example, the processing moduleidentifies embedded devices (e.g., including the user devices)associated with the DSN address range assignments (e.g., based on anaccess control list where an embedded device is authorized to access theDSN with regards to the DSN address range assignments).

The method continues at step 600 where the processing module outputs theregistry information to one or more DS processing units associated withthe old vaults. For example, the processing module identifies the DSprocessing units associated with the DSN address range assignments basedon previous registry information. The method continues at step 602 wherethe processing module suspends operation of the old vaults and activatesoperation the new vaults. For example, the processing module issuesupdated registry information that indicates that the old vaults havebeen replaced by the new vaults such that all entities of the system areto start utilizing the new vaults and suspend operations of the oldvaults.

FIG. 50A is a schematic block diagram of another embodiment of adispersed storage network that includes the storage module 492 of FIG.46A and the storage unit set 494 of FIG. 46A, where the storage unit set494 includes a set of storage units 418 of FIG. 44A. The storage module492 functions to facilitate conversion of data stored in the storageunit set 494 from an old storage format type to a new storage formattype. The storage module 492 receives a read request for a data object,where the data object is encoded using a dispersed storage error codingfunction to produce slices and the slices are stored by the storageunits 418 using the old storage format. The storage module identifies anew storage format of a vault associated with the data object. Forexample, the storage module performs at least one of a lookup, adetermination, and a receive operation.

The storage module 492 issues new type read requests 604 to the storageunit set 494, where the new type read requests 604 indicate the newstorage format such that a storage unit 418 attempts to recover acorresponding slice by retrieving an associated data file from memory ofthe storage unit using the new storage format type. The storage unit 418issues a new type read response 606 to the storage module 492 indicatingwhether the slice was recoverable using the new storage format. Thestorage module 492 issues old type read requests 608 to the storage unitset 494 when receiving new type read response 606 that indicates thatthe slices are unrecoverable using the new storage format. For example,the storage module 492 identifies a field type storage format based onat least one of a lookup, issuing a query, and receiving a formatindicator.

The storage module 492 receives old type read responses 610 from thestorage unit set 494, where the old type read responses 610 includesrecovered slices of the data object. The storage module 492 obtains oneor more sets of slices based on the received recovered slices of thedata object. For example, the storage module 492 decodes received sliceswhen receiving a full set. As another example, the storage module 492rebuilds missing slices when missing slices are detected. The storagemodule 492 issues a new type write requests 612 to the storage unit set,where the new type write requests 612 includes the one or more sets ofslices. Alternatively, the storage module 492 issues a migration requestto the storage unit set 494 such that each storage unit 418 convertscorresponding slices from the old storage format to the new storageformat.

When the storage module 492 has received a sufficient number offavorable new type write responses 614 (e.g., a write threshold numberper set thus confirming storage), the storage module 492 issues old typedelete requests 616 to the storage unit set 494 such that each storageunit 418 deletes the data files associated with the old storage formatthat were utilized to store the corresponding slices. The storage module492 indicates that the process has completed when receiving a favorablenumber of old type delete responses 618 indicating that the data filesassociated with the old storage format have been deleted.

FIG. 50B is a flowchart illustrating an example of converting a storageformat type. The method begins with step 620 where a processing module(e.g., of a storage module) receives a read request for a data object,where the data object is stored in accordance with an old storage formattype as slices in a set of storage units. The method continues at step622 where the processing module identifies a newest storage format typeassociated with the data object. For example, the processing moduleidentifies a vault by accessing registry information and/or vaultinformation to identify the newest format associated with the vault. Themethod continues at step 624 where the processing module issues newesttype read requests to the storage unit set. Storage units of the storageunit set issue a new type read response to the storage module indicatingwhether a corresponding slice was recoverable using the newest storageformat.

The method continues at step 626 where the processing module issues oldtype read requests to the storage unit set when newest type readresponses indicate that the data object is unrecoverable using thenewest type. For example, the processing module receives unfavorable newtype read responses, identifies an old storage format type, generatesthe old type read requests, and sends the old type read requests to thestorage unit set. The method continues at step 628 where the processingmodule decodes recovered slices of the received old type read responsesto reproduce a data object. For example, the processing module receivesthe old type read responses and decodes the slices using the dispersedstorage error coding function to reproduce the data object.

The method continues at step 630 where the processing module obtainsslices of the data object. For example, the processing module utilizesreceived slices. As another example, the processing module rebuildsmissing slices from other slices of the data object. The methodcontinues at step 632 where the processing module issues new type writerequests that includes the slices of the data object to the storage unitset. Alternatively, the processing module issues a migration request tothe storage unit set. When receiving a favorable number of new typewrite responses, the method continues at step 634 where the processingmodule issues old type delete requests to the storage unit set. Forexample, the processing module receives new type write responses,indicates favorable when at least a write threshold number of favorablenew type write responses have been received for each set of a pluralityof sets of slices, and generates old type delete requests.

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “operably coupled to”, “coupled to”, and/or “coupling” includesdirect coupling between items and/or indirect coupling between items viaan intervening item (e.g., an item includes, but is not limited to, acomponent, an element, a circuit, and/or a module) where, for indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.As may even further be used herein, the term “operable to” or “operablycoupled to” indicates that an item includes one or more of powerconnections, input(s), output(s), etc., to perform, when activated, oneor more its corresponding functions and may further include inferredcoupling to one or more other items. As may still further be usedherein, the term “associated with”, includes direct and/or indirectcoupling of separate items and/or one item being embedded within anotheritem. As may be used herein, the term “compares favorably”, indicatesthat a comparison between two or more items, signals, etc., provides adesired relationship. For example, when the desired relationship is thatsignal 1 has a greater magnitude than signal 2, a favorable comparisonmay be achieved when the magnitude of signal 1 is greater than that ofsignal 2 or when the magnitude of signal 2 is less than that of signal1.

As may also be used herein, the terms “processing module”, “processingcircuit”, and/or “processing unit” may be a single processing device ora plurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module, module, processingcircuit, and/or processing unit may be, or further include, memoryand/or an integrated memory element, which may be a single memorydevice, a plurality of memory devices, and/or embedded circuitry ofanother processing module, module, processing circuit, and/or processingunit. Such a memory device may be a read-only memory, random accessmemory, volatile memory, non-volatile memory, static memory, dynamicmemory, flash memory, cache memory, and/or any device that storesdigital information. Note that if the processing module, module,processing circuit, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

The present invention has been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claimed invention. Further, theboundaries of these functional building blocks have been arbitrarilydefined for convenience of description. Alternate boundaries could bedefined as long as the certain significant functions are appropriatelyperformed. Similarly, flow diagram blocks may also have been arbitrarilydefined herein to illustrate certain significant functionality. To theextent used, the flow diagram block boundaries and sequence could havebeen defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claimed invention. One of average skill in the artwill also recognize that the functional building blocks, and otherillustrative blocks, modules and components herein, can be implementedas illustrated or by discrete components, application specificintegrated circuits, processors executing appropriate software and thelike or any combination thereof.

The present invention may have also been described, at least in part, interms of one or more embodiments. An embodiment of the present inventionis used herein to illustrate the present invention, an aspect thereof, afeature thereof, a concept thereof, and/or an example thereof. Aphysical embodiment of an apparatus, an article of manufacture, amachine, and/or of a process that embodies the present invention mayinclude one or more of the aspects, features, concepts, examples, etc.described with reference to one or more of the embodiments discussedherein. Further, from figure to figure, the embodiments may incorporatethe same or similarly named functions, steps, modules, etc. that may usethe same or different reference numbers and, as such, the functions,steps, modules, etc. may be the same or similar functions, steps,modules, etc. or different ones.

While the transistors in the above described figure(s) is/are shown asfield effect transistors (FETs), as one of ordinary skill in the artwill appreciate, the transistors may be implemented using any type oftransistor structure including, but not limited to, bipolar, metal oxidesemiconductor field effect transistors (MOSFET), N-well transistors,P-well transistors, enhancement mode, depletion mode, and zero voltagethreshold (VT) transistors.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of the various embodimentsof the present invention. A module includes a processing module, afunctional block, hardware, and/or software stored on memory forperforming one or more functions as may be described herein. Note that,if the module is implemented via hardware, the hardware may operateindependently and/or in conjunction software and/or firmware. As usedherein, a module may contain one or more sub-modules, each of which maybe one or more modules.

While particular combinations of various functions and features of thepresent invention have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent invention is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by one or more processingmodules of one or more computing devices of a dispersed storage network(DSN), the method comprises: transmitting a set of write commands forstoring a set of encoded data slices in storage units of the DSN,wherein a data segment is dispersed storage error encoded into the setof encoded data slices, wherein the set of encoded data slices includesa total number of encoded data slices, wherein a threshold number ofencoded data slices is needed to recover the data segment, and whereinthe threshold number is less than the total number; determining whetherat least a first threshold number of write responses have been receivedwithin a first response time period; when the at least the firstthreshold number of the write responses have been received within thefirst response time period and the at least the first threshold numberis less than the total number, determining whether at least a secondthreshold number of the write responses have been received within asecond response time period, wherein the first threshold number is lessthan the second threshold number and wherein the second response timeperiod is subsequent to the first response time period; when the atleast the second threshold number of the write responses have beenreceived within the second response time period and the at least thesecond threshold number is less than the total number, determiningwhether the total number of write responses have been received within athird response time period, wherein the second threshold number is lessthan the total number and wherein the third response time period issubsequent to the second response time period; and when the total numberof write responses have not been received within the third response timeperiod, issuing a sub-set of write commit commands corresponding to aresponse number of encoded data slices for which a write response wasreceived, wherein the response number is less than the total number andis equal to or greater than the at least the second threshold number. 2.The method of claim 1 further comprises: when the at least the firstthreshold number of the write responses have not been received withinthe first response time period, indicating a write failure.
 3. Themethod of claim 1 further comprises: when the at least the firstthreshold number of the write responses have been received within thefirst response time period and the at least the first threshold numberis equal to the total number, issuing a set of write commit commandscorresponding to the set of encoded data slices.
 4. The method of claim1 further comprises: when the at least the second threshold number ofthe write responses have not been received within the second responsetime period, issuing a second sub-set of write commit commandscorresponding to a second response number of encoded data slices forwhich the write response was received prior to expiration of the secondresponse time period.
 5. The method of claim 1 further comprises: whenthe at least the second threshold number of the write responses havebeen received within the second response time period and the at leastthe second threshold number is equal to the total number, issuing a setof write commit commands corresponding to the set of encoded dataslices.
 6. The method of claim 1 further comprises: when the totalnumber of write responses have been received within the third responsetime period, issuing a set of write commit commands corresponding to theset of encoded data slices.
 7. The method of claim 1 further comprises:prior to expiration of the third response time period, determiningwhether at least a fourth threshold number of write responses have beenreceived within a fourth response time period, wherein the fourththreshold number is less than the total number and wherein the fourthresponse time period is a portion of the third response time period andis subsequent to the second response time period; and when the at leastthe fourth threshold number of the write responses have been receivedwithin the fourth response time period and the at least the fourththreshold number is less than the total number, determining whether thetotal number of write responses have been received within the thirdresponse time period.
 8. The method of claim 1 further comprises:pre-establishing the first, second, and third response time periods. 9.The method of claim 1 further comprises: determining the second responsetime period based on the first response time period and the receiving ofthe at least the first threshold number of write responses; anddetermining the third response time period based on the receiving of theat least the second threshold number of write responses.
 10. A dispersedstorage (DS) module of a dispersed storage network (DSN), the DS modulecomprises: a first module, when operable within a computing device,causes the computing device to: transmit a set of write commands forstoring a set of encoded data slices in storage units of the DSN,wherein a data segment is dispersed storage error encoded into the setof encoded data slices, wherein the set of encoded data slices includesa total number of encoded data slices, wherein a threshold number ofencoded data slices is needed to recover the data segment, and whereinthe threshold number is less than the total number; a second module,when operable within the computing device, causes the computing deviceto: determine whether at least a first threshold number of writeresponses have been received within a first response time period; athird module, when operable within the computing device, causes thecomputing device to: when the at least the first threshold number of thewrite responses have been received within the first response time periodand the at least the first threshold number is less than the totalnumber, determine whether at least a second threshold number of thewrite responses have been received within a second response time period,wherein the first threshold number is less than the second thresholdnumber and wherein the second response time period is subsequent to thefirst response time period; a fourth module, when operable within thecomputing device, causes the computing device to: when the at least thesecond threshold number of the write responses have been received withinthe second response time period and the at least the second thresholdnumber is less than the total number, determine whether the total numberof write responses have been received within a third response timeperiod, wherein the second threshold number is less than the totalnumber and wherein the third response time period is subsequent to thesecond response time period; and a fifth module, when operable withinthe computing device, causes the computing device to: when the totalnumber of write responses have not been received within the thirdresponse time period, issue a sub-set of write commit commandscorresponding to a response number of encoded data slices for which awrite response was received, wherein the response number is less thanthe total number and is equal to or greater than the at least the secondthreshold number.
 11. The DS module of claim 10 further comprises: thesecond module, when operable within the computing device, further causesthe computing device to: when the at least the first threshold number ofthe write responses have not been received within the first responsetime period, indicate a write failure.
 12. The DS module of claim 10further comprises: the second module, when operable within the computingdevice, further causes the computing device to: when the at least thefirst threshold number of the write responses have been received withinthe first response time period and the at least the first thresholdnumber is equal to the total number, issue a set of write commitcommands corresponding to the set of encoded data slices.
 13. The DSmodule of claim 10 further comprises: the third module, when operablewithin the computing device, further causes the computing device to:when the at least the second threshold number of the write responseshave not been received within the second response time period, issue asecond sub-set of write commit commands corresponding to a secondresponse number of encoded data slices for which the write response wasreceived prior to expiration of the second response time period.
 14. TheDS module of claim 10 further comprises: the third module, when operablewithin the computing device, further causes the computing device to:when the at least the second threshold number of the write responseshave been received within the second response time period and the atleast the second threshold number is equal to the total number, issue aset of write commit commands corresponding to the set of encoded dataslices.
 15. The DS module of claim 10 further comprises: the fourthmodule, when operable within the computing device, further causes thecomputing device to: when the total number of write responses have beenreceived within the third response time period, issue a set of writecommit commands corresponding to the set of encoded data slices.
 16. TheDS module of claim 10 further comprises: the fourth module, whenoperable within the computing device, further causes the computingdevice to: prior to expiration of the third response time period,determine whether at least a fourth threshold number of write responseshave been received within a fourth response time period, wherein thefourth threshold number is less than the total number and wherein thefourth response time period is a portion of the third response timeperiod and is subsequent to the second response time period; and whenthe at least the fourth threshold number of the write responses havebeen received within the fourth response time period and the at leastthe fourth threshold number is less than the total number, determinewhether the total number of write responses have been received withinthe third response time period.
 17. The DS module of claim 10 furthercomprises: a sixth module, when operable within the computing device,causes the computing device to: pre-establish the first, second, andthird response time periods.
 18. The DS module of claim 10 furthercomprises: a sixth module, when operable within the computing device,causes the computing device to: determine the second response timeperiod based on the first response time period and the receiving of theat least the first threshold number of write responses; and determinethe third response time period based on the receiving of the at leastthe second threshold number of write responses.